From db9ae6a0c9cecb92048fde6f06af1da183c09b5f Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 19 Nov 2020 15:41:24 +0100 Subject: Depend on parallel, doc improvements By depending on parallel instead of importing it, functions to set up and stop a cluster are always available when mkin is loaded. The use of multicore processing in mmkin on Windows is now documented in the help file, which brings mkin closer to a version 1.0 #9. --- docs/dev/reference/AIC.mmkin.html | 41 +- docs/dev/reference/D24_2014.html | 251 +++++++++++ docs/dev/reference/DFOP.solution-1.png | Bin 19369 -> 31078 bytes docs/dev/reference/DFOP.solution.html | 13 +- docs/dev/reference/FOMC.solution-1.png | Bin 18630 -> 28900 bytes docs/dev/reference/FOMC.solution.html | 13 +- docs/dev/reference/HS.solution-1.png | Bin 18893 -> 29354 bytes docs/dev/reference/HS.solution.html | 13 +- docs/dev/reference/IORE.solution-1.png | Bin 18668 -> 30028 bytes docs/dev/reference/IORE.solution.html | 33 +- docs/dev/reference/Rplot001.png | Bin 1011 -> 14324 bytes docs/dev/reference/Rplot002.png | Bin 16843 -> 56035 bytes docs/dev/reference/Rplot003.png | Bin 28735 -> 55725 bytes docs/dev/reference/Rplot004.png | Bin 49269 -> 57095 bytes docs/dev/reference/Rplot005.png | Bin 57095 -> 56740 bytes docs/dev/reference/Rplot006.png | Bin 13474 -> 56330 bytes docs/dev/reference/Rplot007.png | Bin 18546 -> 25161 bytes docs/dev/reference/SFO.solution-1.png | Bin 18661 -> 29201 bytes docs/dev/reference/SFO.solution.html | 13 +- docs/dev/reference/SFORB.solution-1.png | Bin 20190 -> 31408 bytes docs/dev/reference/SFORB.solution.html | 13 +- docs/dev/reference/add_err-1.png | Bin 111359 -> 111360 bytes docs/dev/reference/add_err.html | 4 +- docs/dev/reference/confint.mkinfit.html | 225 +++++----- docs/dev/reference/create_deg_func.html | 56 +-- docs/dev/reference/experimental_data_for_UBA-1.png | Bin 107152 -> 103559 bytes docs/dev/reference/experimental_data_for_UBA.html | 85 ++-- docs/dev/reference/f_time_norm_focus.html | 283 +++++++++++++ docs/dev/reference/focus_soil_moisture.html | 206 +++++++++ docs/dev/reference/ilr.html | 44 +- docs/dev/reference/index.html | 63 ++- docs/dev/reference/logLik.mkinfit.html | 30 +- docs/dev/reference/logistic.solution-1.png | Bin 80598 -> 80293 bytes docs/dev/reference/logistic.solution-2.png | Bin 29336 -> 43807 bytes docs/dev/reference/logistic.solution.html | 67 +-- docs/dev/reference/max_twa_parent.html | 26 +- docs/dev/reference/mkinds.html | 63 +-- docs/dev/reference/mkindsg.html | 460 +++++++++++++++++++++ docs/dev/reference/mkinerrplot-1.png | Bin 41458 -> 41094 bytes docs/dev/reference/mkinerrplot.html | 46 ++- docs/dev/reference/mkinfit.html | 20 +- docs/dev/reference/mkinmod.html | 164 ++++++-- docs/dev/reference/mkinparplot-1.png | Bin 16468 -> 25707 bytes docs/dev/reference/mkinparplot.html | 24 +- docs/dev/reference/mkinpredict.html | 6 +- docs/dev/reference/mkinresplot-1.png | Bin 14861 -> 23819 bytes docs/dev/reference/mkinresplot.html | 48 ++- docs/dev/reference/mkinsub.html | 34 +- docs/dev/reference/mmkin.html | 28 +- docs/dev/reference/nafta-1.png | Bin 41379 -> 64838 bytes docs/dev/reference/nafta.html | 22 +- docs/dev/reference/nlme-1.png | Bin 68086 -> 69449 bytes docs/dev/reference/nlme-2.png | Bin 86504 -> 89236 bytes docs/dev/reference/nlme.html | 18 +- docs/dev/reference/nlme.mmkin.html | 12 +- docs/dev/reference/parms.html | 67 +-- docs/dev/reference/plot.mixed.mmkin-3.png | Bin 164014 -> 162677 bytes docs/dev/reference/plot.mixed.mmkin.html | 4 +- docs/dev/reference/plot.mkinfit-1.png | Bin 53973 -> 53731 bytes docs/dev/reference/plot.mkinfit-2.png | Bin 75079 -> 73830 bytes docs/dev/reference/plot.mkinfit-3.png | Bin 70266 -> 69215 bytes docs/dev/reference/plot.mkinfit-4.png | Bin 74166 -> 73285 bytes docs/dev/reference/plot.mkinfit-5.png | Bin 68692 -> 68646 bytes docs/dev/reference/plot.mkinfit-6.png | Bin 75012 -> 74042 bytes docs/dev/reference/plot.mkinfit-7.png | Bin 75692 -> 75294 bytes docs/dev/reference/plot.mkinfit.html | 123 +++--- docs/dev/reference/plot.mmkin-1.png | Bin 34584 -> 50628 bytes docs/dev/reference/plot.mmkin-2.png | Bin 34972 -> 50911 bytes docs/dev/reference/plot.mmkin-3.png | Bin 32445 -> 47267 bytes docs/dev/reference/plot.mmkin-4.png | Bin 25896 -> 34181 bytes docs/dev/reference/plot.mmkin-5.png | Bin 39246 -> 58620 bytes docs/dev/reference/plot.mmkin.html | 59 +-- docs/dev/reference/saem-5.png | Bin 164443 -> 163636 bytes docs/dev/reference/saem-6.png | Bin 0 -> 164696 bytes docs/dev/reference/saem.html | 244 +++++++++-- docs/dev/reference/summary.mkinfit.html | 6 +- docs/dev/reference/summary.nlme.mmkin.html | 23 +- docs/dev/reference/summary.saem.mmkin.html | 357 ++++++++-------- docs/dev/reference/transform_odeparms.html | 2 +- 79 files changed, 2489 insertions(+), 820 deletions(-) create mode 100644 docs/dev/reference/D24_2014.html create mode 100644 docs/dev/reference/f_time_norm_focus.html create mode 100644 docs/dev/reference/focus_soil_moisture.html create mode 100644 docs/dev/reference/mkindsg.html create mode 100644 docs/dev/reference/saem-6.png (limited to 'docs/dev/reference') diff --git a/docs/dev/reference/AIC.mmkin.html b/docs/dev/reference/AIC.mmkin.html index a1418b82..b332257e 100644 --- a/docs/dev/reference/AIC.mmkin.html +++ b/docs/dev/reference/AIC.mmkin.html @@ -73,7 +73,7 @@ same dataset." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -121,7 +121,7 @@ same dataset." />
  • - + @@ -140,7 +140,7 @@ mkinmod." />

    Function to set up a kinetic submodel for one state variable

    - Source: R/mkinsub.R + Source: R/mkinsub.R
    @@ -149,7 +149,7 @@ mkinmod." /> mkinmod.

    - 
    mkinsub(submodel, to = NULL, sink = TRUE, full_name = NA)
    + 
    mkinsub(submodel, to = NULL, sink = TRUE, full_name = NA)

    Arguments

    @@ -181,22 +181,28 @@ results on other operating systems or system configurations.

    Value

    A list for use with mkinmod.

    +

    Author

    + +

    Johannes Ranke

    Examples

    
 # One parent compound, one metabolite, both single first order.
-SFO_SFO <- mkinmod(
-  parent = list(type = "SFO", to = "m1"),
-  m1 = list(type = "SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    
+SFO_SFO <- mkinmod(
+  parent = list(type = "SFO", to = "m1"),
+  m1 = list(type = "SFO"))
+
    #> Successfully compiled differential equation model from auto-generated C code.
    
 # The same model using mkinsub
-SFO_SFO.2 <- mkinmod(
-  parent = mkinsub("SFO", "m1"),
-  m1 = mkinsub("SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    
+SFO_SFO.2 <- mkinmod(
+  parent = mkinsub("SFO", "m1"),
+  m1 = mkinsub("SFO"))
+
    #> Successfully compiled differential equation model from auto-generated C code.
    
 # \dontrun{
   # Now supplying full names
-  SFO_SFO.2 <- mkinmod(
-    parent = mkinsub("SFO", "m1", full_name = "Test compound"),
-    m1 = mkinsub("SFO", full_name = "Metabolite M1"))
    #> Successfully compiled differential equation model from auto-generated C code.
     # }
+  SFO_SFO.2 <- mkinmod(
+    parent = mkinsub("SFO", "m1", full_name = "Test compound"),
+    m1 = mkinsub("SFO", full_name = "Metabolite M1"))
+
    #> Successfully compiled differential equation model from auto-generated C code.
     # }
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/mmkin.html b/docs/dev/reference/mmkin.html index b0ca90f0..4786b02e 100644 --- a/docs/dev/reference/mmkin.html +++ b/docs/dev/reference/mmkin.html @@ -227,9 +227,9 @@ plotting.

    time_default
    #> user system elapsed -#> 4.706 0.488 1.375
    time_1 +#> 4.664 0.433 1.317
    time_1
    #> user system elapsed -#> 5.232 0.005 5.238
    +#> 5.326 0.001 5.330
    endpoints(fits.0[["SFO_lin", 2]])
    #> $ff #> parent_M1 parent_sink M1_M2 M1_sink @@ -252,7 +252,29 @@ plotting.

    # Plotting with mmkin (single brackets, extracting an mmkin object) does not# allow to plot the observed variables separatelyplot(fits.0[1, 1]) -
    # } +
    +# On Windows, we can use multiple cores by making a cluster using the parallel +# package, which gets loaded with mkin, and passing it to mmkin, e.g. +cl <- makePSOCKcluster(12) +f <- mmkin(c("SFO", "FOMC", "DFOP"), + list(A = FOCUS_2006_A, B = FOCUS_2006_B, C = FOCUS_2006_C, D = FOCUS_2006_D), + cluster = cl, quiet = TRUE) +print(f) +
    #> <mmkin> object +#> Status of individual fits: +#> +#> dataset +#> model A B C D +#> SFO OK OK OK OK +#> FOMC C OK OK OK +#> DFOP OK OK OK OK +#> +#> OK: No warnings +#> C: Optimisation did not converge: +#> false convergence (8)
    # We get false convergence for the FOMC fit to FOCUS_2006_A because this +# dataset is really SFO, and the FOMC fit is overparameterised +stopCluster(cl) +# }
    diff --git a/docs/dev/reference/nafta-1.png b/docs/dev/reference/nafta-1.png index 9025f2bb..4d823d77 100644 Binary files a/docs/dev/reference/nafta-1.png and b/docs/dev/reference/nafta-1.png differ diff --git a/docs/dev/reference/nafta.html b/docs/dev/reference/nafta.html index 690e4827..bbc8797d 100644 --- a/docs/dev/reference/nafta.html +++ b/docs/dev/reference/nafta.html @@ -76,7 +76,7 @@ order of increasing model complexity, i.e. SFO, then IORE, and finally DFOP." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -124,7 +124,7 @@ order of increasing model complexity, i.e. SFO, then IORE, and finally DFOP." />
    • - + @@ -143,7 +143,7 @@ order of increasing model complexity, i.e. SFO, then IORE, and finally DFOP." />

      Evaluate parent kinetics using the NAFTA guidance

      - Source: R/nafta.R + Source: R/nafta.R
      @@ -155,10 +155,10 @@ and plotting.

      order of increasing model complexity, i.e. SFO, then IORE, and finally DFOP.

      - 
      nafta(ds, title = NA, quiet = FALSE, ...)
+    
      nafta(ds, title = NA, quiet = FALSE, ...)
 
 # S3 method for nafta
-print(x, quiet = TRUE, digits = 3, ...)
      
+print(x, quiet = TRUE, digits = 3, ...)

      Arguments

    @@ -211,10 +211,15 @@ Degradation mmkin object containing the fits of the three models. The list element named "title" contains the title of the dataset used. The list element "data" contains the dataset used in the fits.

    +

    Author

    + +

    Johannes Ranke

    Examples

    
-  nafta_evaluation <- nafta(NAFTA_SOP_Appendix_D, cores = 1)
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.00192
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.00258
    #> The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    #> The representative half-life of the IORE model is longer than the one corresponding
    #> to the terminal degradation rate found with the DFOP model.
    #> The representative half-life obtained from the DFOP model may be used
      print(nafta_evaluation)
    #> Sums of squares:
+  nafta_evaluation <- nafta(NAFTA_SOP_Appendix_D, cores = 1)
+
    #> The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    #> The representative half-life of the IORE model is longer than the one corresponding
    #> to the terminal degradation rate found with the DFOP model.
    #> The representative half-life obtained from the DFOP model may be used
      print(nafta_evaluation)
+
    #> Sums of squares:
 #>       SFO      IORE      DFOP 
 #> 1378.6832  615.7730  517.8836 
 #> 
@@ -251,7 +256,8 @@ list element "data" contains the dataset used in the fits.
    
 #> DFOP  429    2380      841
 #> 
 #> Representative half-life:
-#> [1] 841.41
      plot(nafta_evaluation)
    
+#> [1] 841.41
      plot(nafta_evaluation)
+
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/nlme-1.png b/docs/dev/reference/nlme-1.png index 0b34db8f..193722c7 100644 Binary files a/docs/dev/reference/nlme-1.png and b/docs/dev/reference/nlme-1.png differ diff --git a/docs/dev/reference/nlme-2.png b/docs/dev/reference/nlme-2.png index ce932c86..7129c580 100644 Binary files a/docs/dev/reference/nlme-2.png and b/docs/dev/reference/nlme-2.png differ diff --git a/docs/dev/reference/nlme.html b/docs/dev/reference/nlme.html index e21074e7..e109b34e 100644 --- a/docs/dev/reference/nlme.html +++ b/docs/dev/reference/nlme.html @@ -226,28 +226,28 @@ nlme for the case of a single grouping variable ds.

    #> Model: value ~ nlme_f(name, time, parent_0, log_k_parent_sink) #> Data: grouped_data #> AIC BIC logLik -#> 298.2781 307.7372 -144.1391 +#> 252.7798 262.1358 -121.3899 #> #> Random effects: #> Formula: list(parent_0 ~ 1, log_k_parent_sink ~ 1) #> Level: ds #> Structure: Diagonal -#> parent_0 log_k_parent_sink Residual -#> StdDev: 0.9374733 0.7098105 3.83543 +#> parent_0 log_k_parent_sink Residual +#> StdDev: 0.0006768135 0.6800777 2.489397 #> #> Fixed effects: parent_0 + log_k_parent_sink ~ 1 -#> Value Std.Error DF t-value p-value -#> parent_0 101.76838 1.1445444 45 88.91606 0 -#> log_k_parent_sink -3.05444 0.4195622 45 -7.28008 0 +#> Value Std.Error DF t-value p-value +#> parent_0 101.74884 0.6456014 44 157.60321 0 +#> log_k_parent_sink -3.05575 0.4015811 44 -7.60929 0 #> Correlation: #> prnt_0 -#> log_k_parent_sink 0.034 +#> log_k_parent_sink 0.026 #> #> Standardized Within-Group Residuals: #> Min Q1 Med Q3 Max -#> -2.6169360 -0.2185329 0.0574070 0.5720937 3.0459868 +#> -2.1317488 -0.6878121 0.0828385 0.8592270 2.9529864 #> -#> Number of Observations: 49 +#> Number of Observations: 48 #> Number of Groups: 3
    plot(augPred(m_nlme, level = 0:1), layout = c(3, 1))
    # augPred does not work on fits with more than one state # variable diff --git a/docs/dev/reference/nlme.mmkin.html b/docs/dev/reference/nlme.mmkin.html index 05edbde5..84990521 100644 --- a/docs/dev/reference/nlme.mmkin.html +++ b/docs/dev/reference/nlme.mmkin.html @@ -332,12 +332,12 @@ methods that will automatically work on 'nlme.mmkin' objects, such as #> StdDev: 0.002417 21.63 #>
    ds_2 <- lapply(experimental_data_for_UBA_2019[6:10], function(x) x$data[c("name", "time", "value")]) - m_sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"), - A1 = mkinsub("SFO"), use_of_ff = "min", quiet = TRUE) - m_sfo_sfo_ff <- mkinmod(parent = mkinsub("SFO", "A1"), - A1 = mkinsub("SFO"), use_of_ff = "max", quiet = TRUE) - m_dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"), - A1 = mkinsub("SFO"), quiet = TRUE) + m_sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"), + A1 = mkinsub("SFO"), use_of_ff = "min", quiet = TRUE) + m_sfo_sfo_ff <- mkinmod(parent = mkinsub("SFO", "A1"), + A1 = mkinsub("SFO"), use_of_ff = "max", quiet = TRUE) + m_dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"), + A1 = mkinsub("SFO"), quiet = TRUE) f_2 <- mmkin(list("SFO-SFO" = m_sfo_sfo, "SFO-SFO-ff" = m_sfo_sfo_ff, diff --git a/docs/dev/reference/parms.html b/docs/dev/reference/parms.html index bd35d3c1..ba0e89bb 100644 --- a/docs/dev/reference/parms.html +++ b/docs/dev/reference/parms.html @@ -74,7 +74,7 @@ considering the error structure that was assumed for the fit." /> mkin - 0.9.50.3 + 0.9.50.4
    @@ -122,7 +122,7 @@ considering the error structure that was assumed for the fit." />
    • - + @@ -141,7 +141,7 @@ considering the error structure that was assumed for the fit." />

      Extract model parameters from mkinfit models

      - Source: R/parms.mkinfit.R + Source: R/parms.mkinfit.R
      @@ -151,13 +151,13 @@ model parameters, in order to avoid working with a fitted model without considering the error structure that was assumed for the fit.

      - 
      parms(object, ...)
+    
      parms(object, ...)
 
 # S3 method for mkinfit
-parms(object, transformed = FALSE, ...)
+parms(object, transformed = FALSE, ...)
 
 # S3 method for mmkin
-parms(object, transformed = FALSE, ...)
      
+parms(object, transformed = FALSE, ...)

      Arguments

    @@ -187,19 +187,24 @@ such matrices is returned.

    Examples

    # mkinfit objects
-fit <- mkinfit("SFO", FOCUS_2006_C, quiet = TRUE)
-parms(fit)
    #>   parent_0   k_parent      sigma 
-#> 82.4921598  0.3060633  4.6730124 
    parms(fit, transformed = TRUE)
    #>     parent_0 log_k_parent        sigma 
+fit <- mkinfit("SFO", FOCUS_2006_C, quiet = TRUE)
+parms(fit)
+
    #>   parent_0   k_parent      sigma 
+#> 82.4921598  0.3060633  4.6730124 
    parms(fit, transformed = TRUE)
+
    #>     parent_0 log_k_parent        sigma 
 #>    82.492160    -1.183963     4.673012 
    
 # mmkin objects
-ds <- lapply(experimental_data_for_UBA_2019[6:10],
- function(x) subset(x$data[c("name", "time", "value")]))
-names(ds) <- paste("Dataset", 6:10)
+ds <- lapply(experimental_data_for_UBA_2019[6:10],
+ function(x) subset(x$data[c("name", "time", "value")]))
+names(ds) <- paste("Dataset", 6:10)
 # \dontrun{
-fits <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE, cores = 1)
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0195
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.00408
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0492
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.00985
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.00815
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.011
    parms(fits["SFO", ])
    #>            Dataset 6    Dataset 7  Dataset 8  Dataset 9  Dataset 10
+fits <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE, cores = 1)
+parms(fits["SFO", ])
+
    #>            Dataset 6    Dataset 7  Dataset 8  Dataset 9  Dataset 10
 #> parent_0 88.52275400 82.666781678 86.8547308 91.7779306 82.14809450
 #> k_parent  0.05794659  0.009647805  0.2102974  0.1232258  0.00720421
-#> sigma     5.15274487  7.040168584  3.6769645  6.4669234  6.50457673
    parms(fits[, 2])
    #> $SFO
+#> sigma     5.15274487  7.040168584  3.6769645  6.4669234  6.50457673
    parms(fits[, 2])
+
    #> $SFO
 #>             Dataset 7
 #> parent_0 82.666781678
 #> k_parent  0.009647805
@@ -214,12 +219,13 @@ such matrices is returned.
    
 #> 
 #> $DFOP
 #>             Dataset 7
-#> parent_0 91.058971503
+#> parent_0 91.058971597
 #> k1        0.044946770
 #> k2        0.002868336
-#> g         0.526942415
+#> g         0.526942414
 #> sigma     2.221302196
-#> 
    parms(fits)
    #> $SFO
+#> 
    parms(fits)
+
    #> $SFO
 #>            Dataset 6    Dataset 7  Dataset 8  Dataset 9  Dataset 10
 #> parent_0 88.52275400 82.666781678 86.8547308 91.7779306 82.14809450
 #> k_parent  0.05794659  0.009647805  0.2102974  0.1232258  0.00720421
@@ -234,12 +240,13 @@ such matrices is returned.
    
 #> 
 #> $DFOP
 #>            Dataset 6    Dataset 7   Dataset 8   Dataset 9   Dataset 10
-#> parent_0 96.55213663 91.058971503 90.34509469 98.14858850 94.311323409
-#> k1        0.21954589  0.044946770  0.41232289  0.31697588  0.080663853
-#> k2        0.02957934  0.002868336  0.07581767  0.03260384  0.003425417
-#> g         0.44845068  0.526942415  0.66091965  0.65322767  0.342652880
+#> parent_0 96.55213663 91.058971597 90.34509493 98.14858820 94.311323733
+#> k1        0.21954588  0.044946770  0.41232288  0.31697588  0.080663857
+#> k2        0.02957934  0.002868336  0.07581766  0.03260384  0.003425417
+#> g         0.44845068  0.526942414  0.66091967  0.65322767  0.342652880
 #> sigma     1.35690468  2.221302196  1.34169076  2.87159846  1.942067831
-#> 
    parms(fits, transformed = TRUE)
    #> $SFO
+#> 
    parms(fits, transformed = TRUE)
+
    #> $SFO
 #>              Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10
 #> parent_0     88.522754 82.666782 86.854731 91.777931  82.148094
 #> log_k_parent -2.848234 -4.641025 -1.559232 -2.093737  -4.933090
@@ -253,13 +260,13 @@ such matrices is returned.
    
 #> sigma      1.8476712  1.9167519  1.0660627  3.14605557   1.622278
 #> 
 #> $DFOP
-#>           Dataset 6   Dataset 7  Dataset 8  Dataset 9 Dataset 10
-#> parent_0 96.5521366 91.05897150 90.3450947 98.1485885  94.311323
-#> log_k1   -1.5161940 -3.10227638 -0.8859485 -1.1489296  -2.517465
-#> log_k2   -3.5206791 -5.85402317 -2.5794240 -3.4233253  -5.676532
-#> g_ilr    -0.1463234  0.07627854  0.4719196  0.4477805  -0.460676
-#> sigma     1.3569047  2.22130220  1.3416908  2.8715985   1.942068
-#> 
    # }
+#>           Dataset 6  Dataset 7  Dataset 8  Dataset 9 Dataset 10
+#> parent_0 96.5521366 91.0589716 90.3450949 98.1485882 94.3113237
+#> log_k1   -1.5161940 -3.1022764 -0.8859486 -1.1489296 -2.5174647
+#> log_k2   -3.5206791 -5.8540232 -2.5794240 -3.4233253 -5.6765322
+#> g_qlogis -0.2069326  0.1078741  0.6673953  0.6332573 -0.6514943
+#> sigma     1.3569047  2.2213022  1.3416908  2.8715985  1.9420678
+#> 
    # }
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/plot.mixed.mmkin-3.png b/docs/dev/reference/plot.mixed.mmkin-3.png index 67058e6c..d58b9c69 100644 Binary files a/docs/dev/reference/plot.mixed.mmkin-3.png and b/docs/dev/reference/plot.mixed.mmkin-3.png differ diff --git a/docs/dev/reference/plot.mixed.mmkin.html b/docs/dev/reference/plot.mixed.mmkin.html index 4108aea3..6ed7cbba 100644 --- a/docs/dev/reference/plot.mixed.mmkin.html +++ b/docs/dev/reference/plot.mixed.mmkin.html @@ -277,10 +277,10 @@ corresponding model prediction lines for the different datasets.

    f_saem <- saem(f)
    #> Running main SAEM algorithm -#> [1] "Mon Nov 9 17:18:17 2020" +#> [1] "Thu Nov 19 14:51:14 2020" #> .... #> Minimisation finished -#> [1] "Mon Nov 9 17:18:26 2020"
    plot(f_saem) +#> [1] "Thu Nov 19 14:51:24 2020"
    plot(f_saem)
    # }
    diff --git a/docs/dev/reference/plot.mkinfit-1.png b/docs/dev/reference/plot.mkinfit-1.png index c6a415d7..fc195031 100644 Binary files a/docs/dev/reference/plot.mkinfit-1.png and b/docs/dev/reference/plot.mkinfit-1.png differ diff --git a/docs/dev/reference/plot.mkinfit-2.png b/docs/dev/reference/plot.mkinfit-2.png index 5dd3731e..fa99f680 100644 Binary files a/docs/dev/reference/plot.mkinfit-2.png and b/docs/dev/reference/plot.mkinfit-2.png differ diff --git a/docs/dev/reference/plot.mkinfit-3.png b/docs/dev/reference/plot.mkinfit-3.png index 59cf8f8d..28789544 100644 Binary files a/docs/dev/reference/plot.mkinfit-3.png and b/docs/dev/reference/plot.mkinfit-3.png differ diff --git a/docs/dev/reference/plot.mkinfit-4.png b/docs/dev/reference/plot.mkinfit-4.png index d9867952..77b3422f 100644 Binary files a/docs/dev/reference/plot.mkinfit-4.png and b/docs/dev/reference/plot.mkinfit-4.png differ diff --git a/docs/dev/reference/plot.mkinfit-5.png b/docs/dev/reference/plot.mkinfit-5.png index 1109c8df..b4b6528b 100644 Binary files a/docs/dev/reference/plot.mkinfit-5.png and b/docs/dev/reference/plot.mkinfit-5.png differ diff --git a/docs/dev/reference/plot.mkinfit-6.png b/docs/dev/reference/plot.mkinfit-6.png index 230c90e9..f71f1769 100644 Binary files a/docs/dev/reference/plot.mkinfit-6.png and b/docs/dev/reference/plot.mkinfit-6.png differ diff --git a/docs/dev/reference/plot.mkinfit-7.png b/docs/dev/reference/plot.mkinfit-7.png index b23427b5..98fee908 100644 Binary files a/docs/dev/reference/plot.mkinfit-7.png and b/docs/dev/reference/plot.mkinfit-7.png differ diff --git a/docs/dev/reference/plot.mkinfit.html b/docs/dev/reference/plot.mkinfit.html index ffbd1206..3a05a02d 100644 --- a/docs/dev/reference/plot.mkinfit.html +++ b/docs/dev/reference/plot.mkinfit.html @@ -74,7 +74,7 @@ observed data together with the solution of the fitted model." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -122,7 +122,7 @@ observed data together with the solution of the fitted model." />
    • - + @@ -141,7 +141,7 @@ observed data together with the solution of the fitted model." />

      Plot the observed data and the fitted model of an mkinfit object

      - Source: R/plot.mkinfit.R + Source: R/plot.mkinfit.R
      @@ -152,49 +152,49 @@ observed data together with the solution of the fitted model.

      # S3 method for mkinfit
-plot(
-  x,
-  fit = x,
-  obs_vars = names(fit$mkinmod$map),
-  xlab = "Time",
-  ylab = "Observed",
-  xlim = range(fit$data$time),
-  ylim = "default",
-  col_obs = 1:length(obs_vars),
-  pch_obs = col_obs,
-  lty_obs = rep(1, length(obs_vars)),
-  add = FALSE,
-  legend = !add,
-  show_residuals = FALSE,
-  show_errplot = FALSE,
-  maxabs = "auto",
-  sep_obs = FALSE,
-  rel.height.middle = 0.9,
-  row_layout = FALSE,
-  lpos = "topright",
-  inset = c(0.05, 0.05),
-  show_errmin = FALSE,
-  errmin_digits = 3,
-  frame = TRUE,
-  ...
-)
-
-plot_sep(
-  fit,
-  show_errmin = TRUE,
-  show_residuals = ifelse(identical(fit$err_mod, "const"), TRUE, "standardized"),
-  ...
-)
-
-plot_res(
-  fit,
-  sep_obs = FALSE,
-  show_errmin = sep_obs,
-  standardized = ifelse(identical(fit$err_mod, "const"), FALSE, TRUE),
-  ...
-)
-
-plot_err(fit, sep_obs = FALSE, show_errmin = sep_obs, ...)
      +plot( + x, + fit = x, + obs_vars = names(fit$mkinmod$map), + xlab = "Time", + ylab = "Observed", + xlim = range(fit$data$time), + ylim = "default", + col_obs = 1:length(obs_vars), + pch_obs = col_obs, + lty_obs = rep(1, length(obs_vars)), + add = FALSE, + legend = !add, + show_residuals = FALSE, + show_errplot = FALSE, + maxabs = "auto", + sep_obs = FALSE, + rel.height.middle = 0.9, + row_layout = FALSE, + lpos = "topright", + inset = c(0.05, 0.05), + show_errmin = FALSE, + errmin_digits = 3, + frame = TRUE, + ... +) + +plot_sep( + fit, + show_errmin = TRUE, + show_residuals = ifelse(identical(fit$err_mod, "const"), TRUE, "standardized"), + ... +) + +plot_res( + fit, + sep_obs = FALSE, + show_errmin = sep_obs, + standardized = ifelse(identical(fit$err_mod, "const"), FALSE, TRUE), + ... +) + +plot_err(fit, sep_obs = FALSE, show_errmin = sep_obs, ...)

      Arguments

    @@ -314,7 +314,7 @@ chi2 error percentage.

    - + @@ -331,22 +331,35 @@ standardized in the residual plot?

    If the current plot device is a tikz device, then latex is being used for the formatting of the chi2 error level, if show_errmin = TRUE.

    +

    Author

    + +

    Johannes Ranke

    Examples

    
 # One parent compound, one metabolite, both single first order, path from
 # parent to sink included
 # \dontrun{
-SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1", full = "Parent"),
-                   m1 = mkinsub("SFO", full = "Metabolite M1" ))
    #> Successfully compiled differential equation model from auto-generated C code.
    fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
    #> Warning: Observations with value of zero were removed from the data
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
    fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE, error_model = "tc")
    #> Warning: Observations with value of zero were removed from the data
    plot(fit)
    plot_res(fit)
    plot_res(fit, standardized = FALSE)
    plot_err(fit)
    
+SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1", full = "Parent"),
+                   m1 = mkinsub("SFO", full = "Metabolite M1" ))
+
    #> Successfully compiled differential equation model from auto-generated C code.
    fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
+
    #> Warning: Observations with value of zero were removed from the data
    fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE, error_model = "tc")
+
    #> Warning: Observations with value of zero were removed from the data
    plot(fit)
+
    plot_res(fit)
+
    plot_res(fit, standardized = FALSE)
+
    plot_err(fit)
+
    
 # Show the observed variables separately, with residuals
-plot(fit, sep_obs = TRUE, show_residuals = TRUE, lpos = c("topright", "bottomright"),
-     show_errmin = TRUE)
    
+plot(fit, sep_obs = TRUE, show_residuals = TRUE, lpos = c("topright", "bottomright"),
+     show_errmin = TRUE)
+
    
 # The same can be obtained with less typing, using the convenience function plot_sep
-plot_sep(fit, lpos = c("topright", "bottomright"))
    
+plot_sep(fit, lpos = c("topright", "bottomright"))
+
    
 # Show the observed variables separately, with the error model
-plot(fit, sep_obs = TRUE, show_errplot = TRUE, lpos = c("topright", "bottomright"),
-     show_errmin = TRUE)
    # }
+plot(fit, sep_obs = TRUE, show_errplot = TRUE, lpos = c("topright", "bottomright"),
+     show_errmin = TRUE)
+
    # }
    @@ -364,7 +377,7 @@ latex is being used for the formatting of the chi2 error level, if
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/plot.mmkin-1.png b/docs/dev/reference/plot.mmkin-1.png index 24fa6ca7..438d5a53 100644 Binary files a/docs/dev/reference/plot.mmkin-1.png and b/docs/dev/reference/plot.mmkin-1.png differ diff --git a/docs/dev/reference/plot.mmkin-2.png b/docs/dev/reference/plot.mmkin-2.png index 377e50b5..ee04b3c4 100644 Binary files a/docs/dev/reference/plot.mmkin-2.png and b/docs/dev/reference/plot.mmkin-2.png differ diff --git a/docs/dev/reference/plot.mmkin-3.png b/docs/dev/reference/plot.mmkin-3.png index 3ea7b38a..e06ed002 100644 Binary files a/docs/dev/reference/plot.mmkin-3.png and b/docs/dev/reference/plot.mmkin-3.png differ diff --git a/docs/dev/reference/plot.mmkin-4.png b/docs/dev/reference/plot.mmkin-4.png index 017fbd1d..5869df55 100644 Binary files a/docs/dev/reference/plot.mmkin-4.png and b/docs/dev/reference/plot.mmkin-4.png differ diff --git a/docs/dev/reference/plot.mmkin-5.png b/docs/dev/reference/plot.mmkin-5.png index e7463916..927c573b 100644 Binary files a/docs/dev/reference/plot.mmkin-5.png and b/docs/dev/reference/plot.mmkin-5.png differ diff --git a/docs/dev/reference/plot.mmkin.html b/docs/dev/reference/plot.mmkin.html index f02e2ea6..32da836d 100644 --- a/docs/dev/reference/plot.mmkin.html +++ b/docs/dev/reference/plot.mmkin.html @@ -76,7 +76,7 @@ the fit of at least one model to the same dataset is shown." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -124,7 +124,7 @@ the fit of at least one model to the same dataset is shown." />
    • - + @@ -144,31 +144,31 @@ the fit of at least one model to the same dataset is shown." />

      Plot model fits (observed and fitted) and the residuals for a row or column of an mmkin object

      - Source: R/plot.mmkin.R + Source: R/plot.mmkin.R
      -

      When x is a row selected from an mmkin object ([.mmkin), the +

      When x is a row selected from an mmkin object ([.mmkin), the same model fitted for at least one dataset is shown. When it is a column, the fit of at least one model to the same dataset is shown.

      # S3 method for mmkin
-plot(
-  x,
-  main = "auto",
-  legends = 1,
-  resplot = c("time", "errmod"),
-  standardized = FALSE,
-  show_errmin = TRUE,
-  errmin_var = "All data",
-  errmin_digits = 3,
-  cex = 0.7,
-  rel.height.middle = 0.9,
-  ymax = "auto",
-  ...
-)
      +plot( + x, + main = "auto", + legends = 1, + resplot = c("time", "errmod"), + standardized = FALSE, + show_errmin = TRUE, + errmin_var = "All data", + errmin_digits = 3, + cex = 0.7, + rel.height.middle = 0.9, + ymax = "auto", + ... +)

      Arguments

    ...

    Further arguments passed to plot.

    Further arguments passed to plot.
    standardized
    @@ -240,21 +240,30 @@ than two rows of plots are shown.

    If the current plot device is a tikz device, then latex is being used for the formatting of the chi2 error level.

    +

    Author

    + +

    Johannes Ranke

    Examples

    
   # \dontrun{
   # Only use one core not to offend CRAN checks
-  fits <- mmkin(c("FOMC", "HS"),
-                list("FOCUS B" = FOCUS_2006_B, "FOCUS C" = FOCUS_2006_C), # named list for titles
-                cores = 1, quiet = TRUE, error_model = "tc")
    #> Warning: Optimisation did not converge:
-#> iteration limit reached without convergence (10)
      plot(fits[, "FOCUS C"])
      plot(fits["FOMC", ])
      plot(fits["FOMC", ], show_errmin = FALSE)
    
+  fits <- mmkin(c("FOMC", "HS"),
+                list("FOCUS B" = FOCUS_2006_B, "FOCUS C" = FOCUS_2006_C), # named list for titles
+                cores = 1, quiet = TRUE, error_model = "tc")
+
    #> Warning: Optimisation did not converge:
+#> iteration limit reached without convergence (10)
      plot(fits[, "FOCUS C"])
+
      plot(fits["FOMC", ])
+
      plot(fits["FOMC", ], show_errmin = FALSE)
+
    
   # We can also plot a single fit, if we like the way plot.mmkin works, but then the plot
   # height should be smaller than the plot width (this is not possible for the html pages
   # generated by pkgdown, as far as I know).
-  plot(fits["FOMC", "FOCUS C"]) # same as plot(fits[1, 2])
    
+  plot(fits["FOMC", "FOCUS C"]) # same as plot(fits[1, 2])
+
    
   # Show the error models
-  plot(fits["FOMC", ], resplot = "errmod")
      # }
+  plot(fits["FOMC", ], resplot = "errmod")
+
      # }
    @@ -272,7 +281,7 @@ latex is being used for the formatting of the chi2 error level.

    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/saem-5.png b/docs/dev/reference/saem-5.png index 6e6e0f91..a12f8383 100644 Binary files a/docs/dev/reference/saem-5.png and b/docs/dev/reference/saem-5.png differ diff --git a/docs/dev/reference/saem-6.png b/docs/dev/reference/saem-6.png new file mode 100644 index 00000000..314f9cd9 Binary files /dev/null and b/docs/dev/reference/saem-6.png differ diff --git a/docs/dev/reference/saem.html b/docs/dev/reference/saem.html index d0c3495a..948e1378 100644 --- a/docs/dev/reference/saem.html +++ b/docs/dev/reference/saem.html @@ -247,27 +247,27 @@ using mmkin.

    state.ini =c(parent =100), fixed_initials ="parent", quiet =TRUE)f_saem_p0_fixed<-saem(f_mmkin_parent_p0_fixed)
    #> Running main SAEM algorithm -#> [1] "Wed Nov 11 19:47:58 2020" +#> [1] "Thu Nov 19 14:51:31 2020" #> .... #> Minimisation finished -#> [1] "Wed Nov 11 19:48:00 2020"
    +#> [1] "Thu Nov 19 14:51:33 2020"
    f_mmkin_parent <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE) f_saem_sfo <- saem(f_mmkin_parent["SFO", ])
    #> Running main SAEM algorithm -#> [1] "Wed Nov 11 19:48:01 2020" +#> [1] "Thu Nov 19 14:51:34 2020" #> .... #> Minimisation finished -#> [1] "Wed Nov 11 19:48:03 2020"
    f_saem_fomc <- saem(f_mmkin_parent["FOMC", ]) +#> [1] "Thu Nov 19 14:51:36 2020"
    f_saem_fomc <- saem(f_mmkin_parent["FOMC", ])
    #> Running main SAEM algorithm -#> [1] "Wed Nov 11 19:48:03 2020" +#> [1] "Thu Nov 19 14:51:36 2020" #> .... #> Minimisation finished -#> [1] "Wed Nov 11 19:48:05 2020"
    f_saem_dfop <- saem(f_mmkin_parent["DFOP", ]) +#> [1] "Thu Nov 19 14:51:38 2020"
    f_saem_dfop <- saem(f_mmkin_parent["DFOP", ])
    #> Running main SAEM algorithm -#> [1] "Wed Nov 11 19:48:06 2020" +#> [1] "Thu Nov 19 14:51:39 2020" #> .... #> Minimisation finished -#> [1] "Wed Nov 11 19:48:08 2020"
    +#> [1] "Thu Nov 19 14:51:42 2020"
    # The returned saem.mmkin object contains an SaemixObject, therefore we can use # functions from saemix library(saemix) @@ -313,10 +313,10 @@ using mmkin.

    f_mmkin_parent_tc <- update(f_mmkin_parent, error_model = "tc") f_saem_fomc_tc <- saem(f_mmkin_parent_tc["FOMC", ])
    #> Running main SAEM algorithm -#> [1] "Wed Nov 11 19:48:11 2020" +#> [1] "Thu Nov 19 14:51:44 2020" #> .... #> Minimisation finished -#> [1] "Wed Nov 11 19:48:16 2020"
    compare.saemix(list(f_saem_fomc$so, f_saem_fomc_tc$so)) +#> [1] "Thu Nov 19 14:51:49 2020"
    compare.saemix(list(f_saem_fomc$so, f_saem_fomc_tc$so))
    #> Likelihoods computed by importance sampling
    #> AIC BIC #> 1 467.7096 464.9757 #> 2 469.5208 466.3963
    @@ -327,7 +327,7 @@ using mmkin.

    #> Successfully compiled differential equation model from auto-generated C code.
    dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"), A1 = mkinsub("SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    # The following fit uses analytical solutions for SFO-SFO and DFOP-SFO, -# and compiled ODEs for FOMC, both are fast +# and compiled ODEs for FOMC that are much slower f_mmkin <- mmkin(list( "SFO-SFO" = sfo_sfo, "FOMC-SFO" = fomc_sfo, "DFOP-SFO" = dfop_sfo), ds, quiet = TRUE) @@ -336,15 +336,15 @@ using mmkin.

    # solutions written for mkin this took around four minutes f_saem_sfo_sfo <- saem(f_mmkin["SFO-SFO", ])
    #> Running main SAEM algorithm -#> [1] "Wed Nov 11 19:48:18 2020" +#> [1] "Thu Nov 19 14:51:52 2020" #> .... #> Minimisation finished -#> [1] "Wed Nov 11 19:48:23 2020"
    f_saem_dfop_sfo <- saem(f_mmkin["DFOP-SFO", ]) +#> [1] "Thu Nov 19 14:51:57 2020"
    f_saem_dfop_sfo <- saem(f_mmkin["DFOP-SFO", ])
    #> Running main SAEM algorithm -#> [1] "Wed Nov 11 19:48:23 2020" +#> [1] "Thu Nov 19 14:51:57 2020" #> .... #> Minimisation finished -#> [1] "Wed Nov 11 19:48:32 2020"
    # We can use print, plot and summary methods to check the results +#> [1] "Thu Nov 19 14:52:06 2020"
    # We can use print, plot and summary methods to check the results print(f_saem_dfop_sfo)
    #> Kinetic nonlinear mixed-effects model fit by SAEM #> Structural model: @@ -359,8 +359,6 @@ using mmkin.

    #> 170 observations of 2 variable(s) grouped in 5 datasets #> #> Likelihood computed by importance sampling -#> -#> LL by is "-407.78 (df=13)" #> AIC BIC logLik #> 841.6 836.5 -407.8 #> @@ -385,13 +383,12 @@ using mmkin.

    #> SD.log_k1 1.42027 0.52714 2.3134 #> SD.log_k2 1.90634 0.70934 3.1033 #> SD.g_qlogis 0.44771 -0.86417 1.7596
    plot(f_saem_dfop_sfo) -
    summary(f_saem_dfop_sfo, data = FALSE) -
    #> -#> LL by is "-407.78 (df=13)"
    #> saemix version used for fitting: 3.1.9000 +
    summary(f_saem_dfop_sfo, data = TRUE) +
    #> saemix version used for fitting: 3.1.9000 #> mkin version used for pre-fitting: 0.9.50.4 #> R version used for fitting: 4.0.3 -#> Date of fit: Wed Nov 11 19:48:33 2020 -#> Date of summary: Wed Nov 11 19:48:33 2020 +#> Date of fit: Thu Nov 19 14:52:07 2020 +#> Date of summary: Thu Nov 19 14:52:07 2020 #> #> Equations: #> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -406,7 +403,7 @@ using mmkin.

    #> #> Model predictions using solution type analytical #> -#> Fitted in 9.564 s using 300, 100 iterations +#> Fitted in 10.034 s using 300, 100 iterations #> #> Variance model: Constant variance #> @@ -472,11 +469,206 @@ using mmkin.

    #> Estimated disappearance times: #> DT50 DT90 DT50back DT50_k1 DT50_k2 #> parent 14.11 59.53 17.92 8.717 25.03 -#> A1 319.21 1060.38 NA NA NA
    +#> A1 319.21 1060.38 NA NA NA +#> +#> Data: +#> ds name time observed predicted residual std standardized +#> Dataset 6 parent 0 97.2 95.79523 -1.40477 1.883 -0.745888 +#> Dataset 6 parent 0 96.4 95.79523 -0.60477 1.883 -0.321114 +#> Dataset 6 parent 3 71.1 71.32042 0.22042 1.883 0.117035 +#> Dataset 6 parent 3 69.2 71.32042 2.12042 1.883 1.125873 +#> Dataset 6 parent 6 58.1 56.45256 -1.64744 1.883 -0.874739 +#> Dataset 6 parent 6 56.6 56.45256 -0.14744 1.883 -0.078288 +#> Dataset 6 parent 10 44.4 44.48523 0.08523 1.883 0.045256 +#> Dataset 6 parent 10 43.4 44.48523 1.08523 1.883 0.576224 +#> Dataset 6 parent 20 33.3 29.75774 -3.54226 1.883 -1.880826 +#> Dataset 6 parent 20 29.2 29.75774 0.55774 1.883 0.296141 +#> Dataset 6 parent 34 17.6 19.35710 1.75710 1.883 0.932966 +#> Dataset 6 parent 34 18.0 19.35710 1.35710 1.883 0.720578 +#> Dataset 6 parent 55 10.5 10.48443 -0.01557 1.883 -0.008266 +#> Dataset 6 parent 55 9.3 10.48443 1.18443 1.883 0.628895 +#> Dataset 6 parent 90 4.5 3.78622 -0.71378 1.883 -0.378995 +#> Dataset 6 parent 90 4.7 3.78622 -0.91378 1.883 -0.485188 +#> Dataset 6 parent 112 3.0 1.99608 -1.00392 1.883 -0.533048 +#> Dataset 6 parent 112 3.4 1.99608 -1.40392 1.883 -0.745435 +#> Dataset 6 parent 132 2.3 1.11539 -1.18461 1.883 -0.628990 +#> Dataset 6 parent 132 2.7 1.11539 -1.58461 1.883 -0.841377 +#> Dataset 6 A1 3 4.3 4.66132 0.36132 1.883 0.191849 +#> Dataset 6 A1 3 4.6 4.66132 0.06132 1.883 0.032559 +#> Dataset 6 A1 6 7.0 7.41087 0.41087 1.883 0.218157 +#> Dataset 6 A1 6 7.2 7.41087 0.21087 1.883 0.111964 +#> Dataset 6 A1 10 8.2 9.50878 1.30878 1.883 0.694921 +#> Dataset 6 A1 10 8.0 9.50878 1.50878 1.883 0.801114 +#> Dataset 6 A1 20 11.0 11.69902 0.69902 1.883 0.371157 +#> Dataset 6 A1 20 13.7 11.69902 -2.00098 1.883 -1.062455 +#> Dataset 6 A1 34 11.5 12.67784 1.17784 1.883 0.625396 +#> Dataset 6 A1 34 12.7 12.67784 -0.02216 1.883 -0.011765 +#> Dataset 6 A1 55 14.9 12.78556 -2.11444 1.883 -1.122701 +#> Dataset 6 A1 55 14.5 12.78556 -1.71444 1.883 -0.910314 +#> Dataset 6 A1 90 12.1 11.52954 -0.57046 1.883 -0.302898 +#> Dataset 6 A1 90 12.3 11.52954 -0.77046 1.883 -0.409092 +#> Dataset 6 A1 112 9.9 10.43825 0.53825 1.883 0.285793 +#> Dataset 6 A1 112 10.2 10.43825 0.23825 1.883 0.126503 +#> Dataset 6 A1 132 8.8 9.42830 0.62830 1.883 0.333609 +#> Dataset 6 A1 132 7.8 9.42830 1.62830 1.883 0.864577 +#> Dataset 7 parent 0 93.6 90.91477 -2.68523 1.883 -1.425772 +#> Dataset 7 parent 0 92.3 90.91477 -1.38523 1.883 -0.735514 +#> Dataset 7 parent 3 87.0 84.76874 -2.23126 1.883 -1.184726 +#> Dataset 7 parent 3 82.2 84.76874 2.56874 1.883 1.363919 +#> Dataset 7 parent 7 74.0 77.62735 3.62735 1.883 1.926003 +#> Dataset 7 parent 7 73.9 77.62735 3.72735 1.883 1.979100 +#> Dataset 7 parent 14 64.2 67.52266 3.32266 1.883 1.764224 +#> Dataset 7 parent 14 69.5 67.52266 -1.97734 1.883 -1.049904 +#> Dataset 7 parent 30 54.0 52.41949 -1.58051 1.883 -0.839202 +#> Dataset 7 parent 30 54.6 52.41949 -2.18051 1.883 -1.157783 +#> Dataset 7 parent 60 41.1 39.36582 -1.73418 1.883 -0.920794 +#> Dataset 7 parent 60 38.4 39.36582 0.96582 1.883 0.512818 +#> Dataset 7 parent 90 32.5 33.75388 1.25388 1.883 0.665771 +#> Dataset 7 parent 90 35.5 33.75388 -1.74612 1.883 -0.927132 +#> Dataset 7 parent 120 28.1 30.41716 2.31716 1.883 1.230335 +#> Dataset 7 parent 120 29.0 30.41716 1.41716 1.883 0.752464 +#> Dataset 7 parent 180 26.5 25.66046 -0.83954 1.883 -0.445767 +#> Dataset 7 parent 180 27.6 25.66046 -1.93954 1.883 -1.029832 +#> Dataset 7 A1 3 3.9 2.69355 -1.20645 1.883 -0.640585 +#> Dataset 7 A1 3 3.1 2.69355 -0.40645 1.883 -0.215811 +#> Dataset 7 A1 7 6.9 5.81807 -1.08193 1.883 -0.574470 +#> Dataset 7 A1 7 6.6 5.81807 -0.78193 1.883 -0.415180 +#> Dataset 7 A1 14 10.4 10.22529 -0.17471 1.883 -0.092767 +#> Dataset 7 A1 14 8.3 10.22529 1.92529 1.883 1.022265 +#> Dataset 7 A1 30 14.4 16.75484 2.35484 1.883 1.250345 +#> Dataset 7 A1 30 13.7 16.75484 3.05484 1.883 1.622022 +#> Dataset 7 A1 60 22.1 22.22540 0.12540 1.883 0.066583 +#> Dataset 7 A1 60 22.3 22.22540 -0.07460 1.883 -0.039610 +#> Dataset 7 A1 90 27.5 24.38799 -3.11201 1.883 -1.652376 +#> Dataset 7 A1 90 25.4 24.38799 -1.01201 1.883 -0.537344 +#> Dataset 7 A1 120 28.0 25.53294 -2.46706 1.883 -1.309927 +#> Dataset 7 A1 120 26.6 25.53294 -1.06706 1.883 -0.566572 +#> Dataset 7 A1 180 25.8 26.94943 1.14943 1.883 0.610309 +#> Dataset 7 A1 180 25.3 26.94943 1.64943 1.883 0.875793 +#> Dataset 8 parent 0 91.9 91.53246 -0.36754 1.883 -0.195151 +#> Dataset 8 parent 0 90.8 91.53246 0.73246 1.883 0.388914 +#> Dataset 8 parent 1 64.9 67.73197 2.83197 1.883 1.503686 +#> Dataset 8 parent 1 66.2 67.73197 1.53197 1.883 0.813428 +#> Dataset 8 parent 3 43.5 41.58448 -1.91552 1.883 -1.017081 +#> Dataset 8 parent 3 44.1 41.58448 -2.51552 1.883 -1.335661 +#> Dataset 8 parent 8 18.3 19.62286 1.32286 1.883 0.702395 +#> Dataset 8 parent 8 18.1 19.62286 1.52286 1.883 0.808589 +#> Dataset 8 parent 14 10.2 10.77819 0.57819 1.883 0.306999 +#> Dataset 8 parent 14 10.8 10.77819 -0.02181 1.883 -0.011582 +#> Dataset 8 parent 27 4.9 3.26977 -1.63023 1.883 -0.865599 +#> Dataset 8 parent 27 3.3 3.26977 -0.03023 1.883 -0.016051 +#> Dataset 8 parent 48 1.6 0.48024 -1.11976 1.883 -0.594557 +#> Dataset 8 parent 48 1.5 0.48024 -1.01976 1.883 -0.541460 +#> Dataset 8 parent 70 1.1 0.06438 -1.03562 1.883 -0.549881 +#> Dataset 8 parent 70 0.9 0.06438 -0.83562 1.883 -0.443688 +#> Dataset 8 A1 1 9.6 7.61539 -1.98461 1.883 -1.053761 +#> Dataset 8 A1 1 7.7 7.61539 -0.08461 1.883 -0.044923 +#> Dataset 8 A1 3 15.0 15.47954 0.47954 1.883 0.254622 +#> Dataset 8 A1 3 15.1 15.47954 0.37954 1.883 0.201525 +#> Dataset 8 A1 8 21.2 20.22616 -0.97384 1.883 -0.517076 +#> Dataset 8 A1 8 21.1 20.22616 -0.87384 1.883 -0.463979 +#> Dataset 8 A1 14 19.7 20.00067 0.30067 1.883 0.159645 +#> Dataset 8 A1 14 18.9 20.00067 1.10067 1.883 0.584419 +#> Dataset 8 A1 27 17.5 16.38142 -1.11858 1.883 -0.593929 +#> Dataset 8 A1 27 15.9 16.38142 0.48142 1.883 0.255619 +#> Dataset 8 A1 48 9.5 10.25357 0.75357 1.883 0.400123 +#> Dataset 8 A1 48 9.8 10.25357 0.45357 1.883 0.240833 +#> Dataset 8 A1 70 6.2 5.95728 -0.24272 1.883 -0.128878 +#> Dataset 8 A1 70 6.1 5.95728 -0.14272 1.883 -0.075781 +#> Dataset 9 parent 0 99.8 97.47274 -2.32726 1.883 -1.235697 +#> Dataset 9 parent 0 98.3 97.47274 -0.82726 1.883 -0.439246 +#> Dataset 9 parent 1 77.1 79.72257 2.62257 1.883 1.392500 +#> Dataset 9 parent 1 77.2 79.72257 2.52257 1.883 1.339404 +#> Dataset 9 parent 3 59.0 56.26497 -2.73503 1.883 -1.452212 +#> Dataset 9 parent 3 58.1 56.26497 -1.83503 1.883 -0.974342 +#> Dataset 9 parent 8 27.4 31.66985 4.26985 1.883 2.267151 +#> Dataset 9 parent 8 29.2 31.66985 2.46985 1.883 1.311410 +#> Dataset 9 parent 14 19.1 22.39789 3.29789 1.883 1.751071 +#> Dataset 9 parent 14 29.6 22.39789 -7.20211 1.883 -3.824090 +#> Dataset 9 parent 27 10.1 14.21758 4.11758 1.883 2.186301 +#> Dataset 9 parent 27 18.2 14.21758 -3.98242 1.883 -2.114537 +#> Dataset 9 parent 48 4.5 7.27921 2.77921 1.883 1.475671 +#> Dataset 9 parent 48 9.1 7.27921 -1.82079 1.883 -0.966780 +#> Dataset 9 parent 70 2.3 3.61470 1.31470 1.883 0.698065 +#> Dataset 9 parent 70 2.9 3.61470 0.71470 1.883 0.379485 +#> Dataset 9 parent 91 2.0 1.85303 -0.14697 1.883 -0.078038 +#> Dataset 9 parent 91 1.8 1.85303 0.05303 1.883 0.028155 +#> Dataset 9 parent 120 2.0 0.73645 -1.26355 1.883 -0.670906 +#> Dataset 9 parent 120 2.2 0.73645 -1.46355 1.883 -0.777099 +#> Dataset 9 A1 1 4.2 3.87843 -0.32157 1.883 -0.170743 +#> Dataset 9 A1 1 3.9 3.87843 -0.02157 1.883 -0.011453 +#> Dataset 9 A1 3 7.4 8.90535 1.50535 1.883 0.799291 +#> Dataset 9 A1 3 7.9 8.90535 1.00535 1.883 0.533807 +#> Dataset 9 A1 8 14.5 13.75172 -0.74828 1.883 -0.397312 +#> Dataset 9 A1 8 13.7 13.75172 0.05172 1.883 0.027462 +#> Dataset 9 A1 14 14.2 14.97541 0.77541 1.883 0.411715 +#> Dataset 9 A1 14 12.2 14.97541 2.77541 1.883 1.473650 +#> Dataset 9 A1 27 13.7 14.94728 1.24728 1.883 0.662266 +#> Dataset 9 A1 27 13.2 14.94728 1.74728 1.883 0.927750 +#> Dataset 9 A1 48 13.6 13.66078 0.06078 1.883 0.032272 +#> Dataset 9 A1 48 15.4 13.66078 -1.73922 1.883 -0.923470 +#> Dataset 9 A1 70 10.4 11.84899 1.44899 1.883 0.769365 +#> Dataset 9 A1 70 11.6 11.84899 0.24899 1.883 0.132204 +#> Dataset 9 A1 91 10.0 10.09177 0.09177 1.883 0.048727 +#> Dataset 9 A1 91 9.5 10.09177 0.59177 1.883 0.314211 +#> Dataset 9 A1 120 9.1 7.91379 -1.18621 1.883 -0.629841 +#> Dataset 9 A1 120 9.0 7.91379 -1.08621 1.883 -0.576745 +#> Dataset 10 parent 0 96.1 93.65257 -2.44743 1.883 -1.299505 +#> Dataset 10 parent 0 94.3 93.65257 -0.64743 1.883 -0.343763 +#> Dataset 10 parent 8 73.9 77.85906 3.95906 1.883 2.102132 +#> Dataset 10 parent 8 73.9 77.85906 3.95906 1.883 2.102132 +#> Dataset 10 parent 14 69.4 70.17143 0.77143 1.883 0.409606 +#> Dataset 10 parent 14 73.1 70.17143 -2.92857 1.883 -1.554974 +#> Dataset 10 parent 21 65.6 63.99188 -1.60812 1.883 -0.853862 +#> Dataset 10 parent 21 65.3 63.99188 -1.30812 1.883 -0.694572 +#> Dataset 10 parent 41 55.9 54.64292 -1.25708 1.883 -0.667467 +#> Dataset 10 parent 41 54.4 54.64292 0.24292 1.883 0.128985 +#> Dataset 10 parent 63 47.0 49.61303 2.61303 1.883 1.387433 +#> Dataset 10 parent 63 49.3 49.61303 0.31303 1.883 0.166207 +#> Dataset 10 parent 91 44.7 45.17807 0.47807 1.883 0.253839 +#> Dataset 10 parent 91 46.7 45.17807 -1.52193 1.883 -0.808096 +#> Dataset 10 parent 120 42.1 41.27970 -0.82030 1.883 -0.435552 +#> Dataset 10 parent 120 41.3 41.27970 -0.02030 1.883 -0.010778 +#> Dataset 10 A1 8 3.3 3.99294 0.69294 1.883 0.367929 +#> Dataset 10 A1 8 3.4 3.99294 0.59294 1.883 0.314832 +#> Dataset 10 A1 14 3.9 5.92756 2.02756 1.883 1.076570 +#> Dataset 10 A1 14 2.9 5.92756 3.02756 1.883 1.607538 +#> Dataset 10 A1 21 6.4 7.47313 1.07313 1.883 0.569799 +#> Dataset 10 A1 21 7.2 7.47313 0.27313 1.883 0.145025 +#> Dataset 10 A1 41 9.1 9.76819 0.66819 1.883 0.354786 +#> Dataset 10 A1 41 8.5 9.76819 1.26819 1.883 0.673367 +#> Dataset 10 A1 63 11.7 10.94733 -0.75267 1.883 -0.399643 +#> Dataset 10 A1 63 12.0 10.94733 -1.05267 1.883 -0.558933 +#> Dataset 10 A1 91 13.3 11.93773 -1.36227 1.883 -0.723321 +#> Dataset 10 A1 91 13.2 11.93773 -1.26227 1.883 -0.670224 +#> Dataset 10 A1 120 14.3 12.77666 -1.52334 1.883 -0.808847 +#> Dataset 10 A1 120 12.1 12.77666 0.67666 1.883 0.359282
    # Using a single core, the following takes about 6 minutes as we do not have an # analytical solution. Using 10 cores it is slower instead of faster -#f_saem_fomc <- saem(f_mmkin["FOMC-SFO", ], cores = 1) -# } +f_saem_fomc <- saem(f_mmkin["FOMC-SFO", ], cores = 1) +
    #> Running main SAEM algorithm +#> [1] "Thu Nov 19 14:52:08 2020" +#> DLSODA- At current T (=R1), MXSTEP (=I1) steps +#> taken on this call before reaching TOUT +#> In above message, I1 = 5000 +#> +#> In above message, R1 = 0.00156238 +#> +#> DLSODA- At T (=R1) and step size H (=R2), the +#> corrector convergence failed repeatedly +#> or with ABS(H) = HMIN +#> In above message, R1 = 0, R2 = 1.1373e-10 +#> +#> DLSODA- At current T (=R1), MXSTEP (=I1) steps +#> taken on this call before reaching TOUT +#> In above message, I1 = 5000 +#> +#> In above message, R1 = 2.24752e-06 +#> +#> .... +#> Minimisation finished +#> [1] "Thu Nov 19 14:59:05 2020"
    plot(f_saem_fomc) +
    # }
    #> mkin version used for fitting: 0.9.50.4 #> R version used for fitting: 4.0.3 -#> Date of fit: Sat Nov 7 13:28:04 2020 -#> Date of summary: Sat Nov 7 13:28:04 2020 +#> Date of fit: Thu Nov 19 14:59:41 2020 +#> Date of summary: Thu Nov 19 14:59:41 2020 #> #> Equations: #> d_parent/dt = - k_parent * parent #> #> Model predictions using solution type analytical #> -#> Fitted using 131 model solutions performed in 0.028 s +#> Fitted using 131 model solutions performed in 0.033 s #> #> Error model: Constant variance #> diff --git a/docs/dev/reference/summary.nlme.mmkin.html b/docs/dev/reference/summary.nlme.mmkin.html index d35e8713..d016796e 100644 --- a/docs/dev/reference/summary.nlme.mmkin.html +++ b/docs/dev/reference/summary.nlme.mmkin.html @@ -265,8 +265,8 @@ José Pinheiro and Douglas Bates for the components inherited from nlme

    #> nlme version used for fitting: 3.1.150.1 #> mkin version used for pre-fitting: 0.9.50.4 #> R version used for fitting: 4.0.3 -#> Date of fit: Sat Nov 7 13:28:06 2020 -#> Date of summary: Sat Nov 7 13:28:06 2020 +#> Date of fit: Thu Nov 19 14:59:43 2020 +#> Date of summary: Thu Nov 19 14:59:43 2020 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -276,7 +276,7 @@ José Pinheiro and Douglas Bates for the components inherited from nlme

    #> #> Model predictions using solution type analytical #> -#> Fitted in 0.588 s using 5 iterations +#> Fitted in 0.681 s using 5 iterations #> #> Variance model: Two-component variance function #> @@ -293,24 +293,20 @@ José Pinheiro and Douglas Bates for the components inherited from nlme

    #> 555.792 570.7908 -271.896 #> #> Optimised, transformed parameters with symmetric confidence intervals: -#> lower est. upper -#> parent_0 94.701336 97.763446 100.82556 -#> log_k_parent -5.007574 -4.461767 -3.91596 +#> lower est. upper +#> parent_0 94.701 97.763 100.826 +#> log_k_parent -5.008 -4.462 -3.916 #> #> Correlation: #> prnt_0 #> log_k_parent 0.024 #> -#> Backtransformed parameters with asymmetric confidence intervals: -#> lower est. upper -#> parent_0 94.701335804 97.76344625 100.82555670 -#> k_parent 0.006687109 0.01154195 0.01992142 #> Random effects: #> Formula: list(parent_0 ~ 1, log_k_parent ~ 1) #> Level: ds #> Structure: Diagonal #> parent_0 log_k_parent Residual -#> StdDev: 16.65969 3.516961 5.709013 +#> StdDev: 2.898 0.6119 1 #> #> Variance function: #> Structure: Constant plus proportion of variance covariate @@ -319,6 +315,11 @@ José Pinheiro and Douglas Bates for the components inherited from nlme

    #> const prop #> 1.55075176 0.05680853 #> +#> Backtransformed parameters with asymmetric confidence intervals: +#> lower est. upper +#> parent_0 94.701336 97.76345 100.82556 +#> k_parent 0.006687 0.01154 0.01992 +#> #> Estimated disappearance times: #> DT50 DT90 #> parent 60.05 199.5 diff --git a/docs/dev/reference/summary.saem.mmkin.html b/docs/dev/reference/summary.saem.mmkin.html index 8a5d001a..b7804247 100644 --- a/docs/dev/reference/summary.saem.mmkin.html +++ b/docs/dev/reference/summary.saem.mmkin.html @@ -260,16 +260,15 @@ saemix authors for the parts inherited from saemix.

    quiet = TRUE, error_model = "tc", cores = 5) f_saem_dfop_sfo <- saem(f_mmkin_dfop_sfo)
    #> Running main SAEM algorithm -#> [1] "Wed Nov 11 19:48:36 2020" +#> [1] "Thu Nov 19 14:59:46 2020" #> .... #> Minimisation finished -#> [1] "Wed Nov 11 19:48:48 2020"
    summary(f_saem_dfop_sfo, data = TRUE) -
    #> -#> LL by is "-401.01 (df=14)"
    #> saemix version used for fitting: 3.1.9000 +#> [1] "Thu Nov 19 15:00:00 2020"
    summary(f_saem_dfop_sfo, data = TRUE) +
    #> saemix version used for fitting: 3.1.9000 #> mkin version used for pre-fitting: 0.9.50.4 #> R version used for fitting: 4.0.3 -#> Date of fit: Wed Nov 11 19:48:49 2020 -#> Date of summary: Wed Nov 11 19:48:49 2020 +#> Date of fit: Thu Nov 19 15:00:01 2020 +#> Date of summary: Thu Nov 19 15:00:01 2020 #> #> Equations: #> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -284,7 +283,7 @@ saemix authors for the parts inherited from saemix.

    #> #> Model predictions using solution type analytical #> -#> Fitted in 13.272 s using 300, 100 iterations +#> Fitted in 15.23 s using 300, 100 iterations #> #> Variance model: Two-component variance function #> @@ -354,178 +353,178 @@ saemix authors for the parts inherited from saemix.

    #> m1 40.60 134.88 NA NA NA #> #> Data: -#> ds name time observed predicted residual standardized -#> ds 1 parent 0 89.8 9.869e+01 -8.894553 1.273163 -#> ds 1 parent 0 104.1 9.869e+01 5.405447 -0.773734 -#> ds 1 parent 1 88.7 9.413e+01 -5.426448 0.810727 -#> ds 1 parent 1 95.5 9.413e+01 1.373552 -0.205213 -#> ds 1 parent 3 81.8 8.576e+01 -3.961821 0.643463 -#> ds 1 parent 3 94.5 8.576e+01 8.738179 -1.419220 -#> ds 1 parent 7 71.5 7.168e+01 -0.184828 0.035175 -#> ds 1 parent 7 70.3 7.168e+01 -1.384828 0.263550 -#> ds 1 parent 14 54.2 5.351e+01 0.688235 -0.168298 -#> ds 1 parent 14 49.6 5.351e+01 -3.911765 0.956565 -#> ds 1 parent 28 31.5 3.209e+01 -0.590445 0.217395 -#> ds 1 parent 28 28.8 3.209e+01 -3.290445 1.211502 -#> ds 1 parent 60 12.1 1.272e+01 -0.618158 0.419377 -#> ds 1 parent 60 13.6 1.272e+01 0.881842 -0.598269 -#> ds 1 parent 90 6.2 6.085e+00 0.115212 -0.109861 -#> ds 1 parent 90 8.3 6.085e+00 2.215212 -2.112329 -#> ds 1 parent 120 2.2 3.009e+00 -0.809439 0.950563 -#> ds 1 parent 120 2.4 3.009e+00 -0.609439 0.715693 -#> ds 1 m1 1 0.3 1.129e+00 -0.828817 1.133869 -#> ds 1 m1 1 0.2 1.129e+00 -0.928817 1.270675 -#> ds 1 m1 3 2.2 3.141e+00 -0.940880 1.094093 -#> ds 1 m1 3 3.0 3.141e+00 -0.140880 0.163821 -#> ds 1 m1 7 6.5 6.326e+00 0.174162 -0.163662 -#> ds 1 m1 7 5.0 6.326e+00 -1.325838 1.245901 -#> ds 1 m1 14 10.2 9.883e+00 0.317417 -0.245642 -#> ds 1 m1 14 9.5 9.883e+00 -0.382583 0.296072 -#> ds 1 m1 28 12.2 1.251e+01 -0.309856 0.212138 -#> ds 1 m1 28 13.4 1.251e+01 0.890144 -0.609422 -#> ds 1 m1 60 11.8 1.086e+01 0.940009 -0.693807 -#> ds 1 m1 60 13.2 1.086e+01 2.340009 -1.727126 -#> ds 1 m1 90 6.6 7.823e+00 -1.222977 1.054158 -#> ds 1 m1 90 9.3 7.823e+00 1.477023 -1.273135 -#> ds 1 m1 120 3.5 5.315e+00 -1.815201 1.816354 -#> ds 1 m1 120 5.4 5.315e+00 0.084799 -0.084853 -#> ds 2 parent 0 118.0 1.031e+02 14.876736 -2.046284 -#> ds 2 parent 0 99.8 1.031e+02 -3.323264 0.457112 -#> ds 2 parent 1 90.2 9.757e+01 -7.371379 1.066126 -#> ds 2 parent 1 94.6 9.757e+01 -2.971379 0.429752 -#> ds 2 parent 3 96.1 8.788e+01 8.222746 -1.306721 -#> ds 2 parent 3 78.4 8.788e+01 -9.477254 1.506081 -#> ds 2 parent 7 77.9 7.293e+01 4.972272 -0.932149 -#> ds 2 parent 7 77.7 7.293e+01 4.772272 -0.894656 -#> ds 2 parent 14 56.0 5.602e+01 -0.016773 0.003947 -#> ds 2 parent 14 54.7 5.602e+01 -1.316773 0.309830 -#> ds 2 parent 28 36.6 3.855e+01 -1.945779 0.621680 -#> ds 2 parent 28 36.8 3.855e+01 -1.745779 0.557779 -#> ds 2 parent 60 22.1 2.101e+01 1.086693 -0.541771 -#> ds 2 parent 60 24.7 2.101e+01 3.686693 -1.838002 -#> ds 2 parent 90 12.4 1.246e+01 -0.058759 0.040319 -#> ds 2 parent 90 10.8 1.246e+01 -1.658759 1.138195 -#> ds 2 parent 120 6.8 7.406e+00 -0.606226 0.534861 -#> ds 2 parent 120 7.9 7.406e+00 0.493774 -0.435647 -#> ds 2 m1 1 1.3 1.438e+00 -0.138236 0.184118 -#> ds 2 m1 3 3.7 3.879e+00 -0.178617 0.196874 -#> ds 2 m1 3 4.7 3.879e+00 0.821383 -0.905344 -#> ds 2 m1 7 8.1 7.389e+00 0.710951 -0.627868 -#> ds 2 m1 7 7.9 7.389e+00 0.510951 -0.451240 -#> ds 2 m1 14 10.1 1.069e+01 -0.593533 0.441556 -#> ds 2 m1 14 10.3 1.069e+01 -0.393533 0.292767 -#> ds 2 m1 28 10.7 1.240e+01 -1.703647 1.171837 -#> ds 2 m1 28 12.2 1.240e+01 -0.203647 0.140077 -#> ds 2 m1 60 10.7 1.055e+01 0.147672 -0.110605 -#> ds 2 m1 60 12.5 1.055e+01 1.947672 -1.458786 -#> ds 2 m1 90 9.1 8.010e+00 1.090041 -0.929963 -#> ds 2 m1 90 7.4 8.010e+00 -0.609959 0.520383 -#> ds 2 m1 120 6.1 5.793e+00 0.306797 -0.297858 -#> ds 2 m1 120 4.5 5.793e+00 -1.293203 1.255523 -#> ds 3 parent 0 106.2 1.035e+02 2.712344 -0.371886 -#> ds 3 parent 0 106.9 1.035e+02 3.412344 -0.467862 -#> ds 3 parent 1 107.4 9.548e+01 11.924044 -1.758752 -#> ds 3 parent 1 96.1 9.548e+01 0.624044 -0.092044 -#> ds 3 parent 3 79.4 8.246e+01 -3.056105 0.514055 -#> ds 3 parent 3 82.6 8.246e+01 0.143895 -0.024204 -#> ds 3 parent 7 63.9 6.489e+01 -0.991141 0.205676 -#> ds 3 parent 7 62.4 6.489e+01 -2.491141 0.516947 -#> ds 3 parent 14 51.0 4.869e+01 2.306824 -0.610198 -#> ds 3 parent 14 47.1 4.869e+01 -1.593176 0.421425 -#> ds 3 parent 28 36.1 3.480e+01 1.304261 -0.451388 -#> ds 3 parent 28 36.6 3.480e+01 1.804261 -0.624431 -#> ds 3 parent 60 20.1 1.988e+01 0.221952 -0.114821 -#> ds 3 parent 60 19.8 1.988e+01 -0.078048 0.040376 -#> ds 3 parent 90 11.3 1.194e+01 -0.642458 0.451083 -#> ds 3 parent 90 10.7 1.194e+01 -1.242458 0.872355 -#> ds 3 parent 120 8.2 7.176e+00 1.023847 -0.915231 -#> ds 3 parent 120 7.3 7.176e+00 0.123847 -0.110709 -#> ds 3 m1 0 0.8 8.527e-13 0.800000 -1.214712 -#> ds 3 m1 1 1.8 1.856e+00 -0.055925 0.071921 -#> ds 3 m1 1 2.3 1.856e+00 0.444075 -0.571099 -#> ds 3 m1 3 4.2 4.780e+00 -0.580164 0.601168 -#> ds 3 m1 3 4.1 4.780e+00 -0.680164 0.704788 -#> ds 3 m1 7 6.8 8.410e+00 -1.609920 1.344090 -#> ds 3 m1 7 10.1 8.410e+00 1.690080 -1.411014 -#> ds 3 m1 14 11.4 1.098e+01 0.424444 -0.311572 -#> ds 3 m1 14 12.8 1.098e+01 1.824444 -1.339271 -#> ds 3 m1 28 11.5 1.142e+01 0.079336 -0.057043 -#> ds 3 m1 28 10.6 1.142e+01 -0.820664 0.590065 -#> ds 3 m1 60 7.5 9.110e+00 -1.610231 1.295778 -#> ds 3 m1 60 8.6 9.110e+00 -0.510231 0.410591 -#> ds 3 m1 90 7.3 6.799e+00 0.501085 -0.457825 -#> ds 3 m1 90 8.1 6.799e+00 1.301085 -1.188759 -#> ds 3 m1 120 5.3 4.868e+00 0.431505 -0.444518 -#> ds 3 m1 120 3.8 4.868e+00 -1.068495 1.100718 -#> ds 4 parent 0 104.7 9.926e+01 5.444622 -0.775351 -#> ds 4 parent 0 88.3 9.926e+01 -10.955378 1.560119 -#> ds 4 parent 1 94.2 9.618e+01 -1.978413 0.289883 -#> ds 4 parent 1 94.6 9.618e+01 -1.578413 0.231274 -#> ds 4 parent 3 78.1 9.037e+01 -12.268550 1.901399 -#> ds 4 parent 3 96.5 9.037e+01 6.131450 -0.950262 -#> ds 4 parent 7 76.2 7.999e+01 -3.794958 0.655739 -#> ds 4 parent 7 77.8 7.999e+01 -2.194958 0.379272 -#> ds 4 parent 14 70.8 6.518e+01 5.624996 -1.162874 -#> ds 4 parent 14 67.3 6.518e+01 2.124996 -0.439307 -#> ds 4 parent 28 43.1 4.462e+01 -1.517860 0.431312 -#> ds 4 parent 28 45.1 4.462e+01 0.482140 -0.137004 -#> ds 4 parent 60 21.3 2.130e+01 0.003305 -0.001633 -#> ds 4 parent 60 23.5 2.130e+01 2.203305 -1.088598 -#> ds 4 parent 90 11.8 1.180e+01 -0.002834 0.002002 -#> ds 4 parent 90 12.1 1.180e+01 0.297166 -0.209966 -#> ds 4 parent 120 7.0 6.868e+00 0.132251 -0.120348 -#> ds 4 parent 120 6.2 6.868e+00 -0.667749 0.607650 -#> ds 4 m1 0 1.6 0.000e+00 1.600000 -2.429424 -#> ds 4 m1 1 0.9 6.826e-01 0.217363 -0.309476 -#> ds 4 m1 3 3.7 1.935e+00 1.765082 -2.255277 -#> ds 4 m1 3 2.0 1.935e+00 0.065082 -0.083157 -#> ds 4 m1 7 3.6 4.035e+00 -0.434805 0.474018 -#> ds 4 m1 7 3.8 4.035e+00 -0.234805 0.255981 -#> ds 4 m1 14 7.1 6.652e+00 0.448187 -0.413053 -#> ds 4 m1 14 6.6 6.652e+00 -0.051813 0.047751 -#> ds 4 m1 28 9.5 9.156e+00 0.343805 -0.276011 -#> ds 4 m1 28 9.3 9.156e+00 0.143805 -0.115448 -#> ds 4 m1 60 8.3 8.848e+00 -0.547762 0.446843 -#> ds 4 m1 60 9.0 8.848e+00 0.152238 -0.124190 -#> ds 4 m1 90 6.6 6.674e+00 -0.073979 0.068090 -#> ds 4 m1 90 7.7 6.674e+00 1.026021 -0.944353 -#> ds 4 m1 120 3.7 4.668e+00 -0.967537 1.010122 -#> ds 4 m1 120 3.5 4.668e+00 -1.167537 1.218925 -#> ds 5 parent 0 110.4 1.022e+02 8.170986 -1.132847 -#> ds 5 parent 0 112.1 1.022e+02 9.870986 -1.368539 -#> ds 5 parent 1 93.5 9.513e+01 -1.630764 0.241319 -#> ds 5 parent 1 91.0 9.513e+01 -4.130764 0.611268 -#> ds 5 parent 3 71.0 8.296e+01 -11.964279 2.001495 -#> ds 5 parent 3 89.7 8.296e+01 6.735721 -1.126813 -#> ds 5 parent 7 60.4 6.495e+01 -4.547441 0.942951 -#> ds 5 parent 7 59.1 6.495e+01 -5.847441 1.212518 -#> ds 5 parent 14 56.5 4.626e+01 10.241319 -2.825682 -#> ds 5 parent 14 47.0 4.626e+01 0.741319 -0.204537 -#> ds 5 parent 28 30.2 3.026e+01 -0.058478 0.022504 -#> ds 5 parent 28 23.9 3.026e+01 -6.358478 2.446932 -#> ds 5 parent 60 17.0 1.792e+01 -0.919046 0.508481 -#> ds 5 parent 60 18.7 1.792e+01 0.780954 -0.432079 -#> ds 5 parent 90 11.3 1.187e+01 -0.573917 0.404206 -#> ds 5 parent 90 11.9 1.187e+01 0.026083 -0.018370 -#> ds 5 parent 120 9.0 7.898e+00 1.102089 -0.946039 -#> ds 5 parent 120 8.1 7.898e+00 0.202089 -0.173474 -#> ds 5 m1 0 0.7 -1.421e-14 0.700000 -1.062873 -#> ds 5 m1 1 3.0 3.144e+00 -0.143526 0.166865 -#> ds 5 m1 1 2.6 3.144e+00 -0.543526 0.631910 -#> ds 5 m1 3 5.1 8.390e+00 -3.290265 2.749870 -#> ds 5 m1 3 7.5 8.390e+00 -0.890265 0.744048 -#> ds 5 m1 7 16.5 1.566e+01 0.841368 -0.506082 -#> ds 5 m1 7 19.0 1.566e+01 3.341368 -2.009830 -#> ds 5 m1 14 22.9 2.188e+01 1.017753 -0.493689 -#> ds 5 m1 14 23.2 2.188e+01 1.317753 -0.639212 -#> ds 5 m1 28 22.2 2.386e+01 -1.655914 0.756794 -#> ds 5 m1 28 24.4 2.386e+01 0.544086 -0.248661 -#> ds 5 m1 60 15.5 1.859e+01 -3.091124 1.670405 -#> ds 5 m1 60 19.8 1.859e+01 1.208876 -0.653262 -#> ds 5 m1 90 14.9 1.372e+01 1.176815 -0.764948 -#> ds 5 m1 90 14.2 1.372e+01 0.476815 -0.309937 -#> ds 5 m1 120 10.9 9.961e+00 0.938796 -0.723690 -#> ds 5 m1 120 10.4 9.961e+00 0.438796 -0.338255
    # } +#> ds name time observed predicted residual std standardized +#> ds 1 parent 0 89.8 9.869e+01 8.894553 6.3618 1.398124 +#> ds 1 parent 0 104.1 9.869e+01 -5.405447 6.3618 -0.849676 +#> ds 1 parent 1 88.7 9.413e+01 5.426448 6.0706 0.893897 +#> ds 1 parent 1 95.5 9.413e+01 -1.373552 6.0706 -0.226265 +#> ds 1 parent 3 81.8 8.576e+01 3.961821 5.5377 0.715422 +#> ds 1 parent 3 94.5 8.576e+01 -8.738179 5.5377 -1.577932 +#> ds 1 parent 7 71.5 7.168e+01 0.184828 4.6429 0.039809 +#> ds 1 parent 7 70.3 7.168e+01 1.384828 4.6429 0.298270 +#> ds 1 parent 14 54.2 5.351e+01 -0.688235 3.4934 -0.197008 +#> ds 1 parent 14 49.6 5.351e+01 3.911765 3.4934 1.119747 +#> ds 1 parent 28 31.5 3.209e+01 0.590445 2.1603 0.273322 +#> ds 1 parent 28 28.8 3.209e+01 3.290445 2.1603 1.523177 +#> ds 1 parent 60 12.1 1.272e+01 0.618158 1.0481 0.589761 +#> ds 1 parent 60 13.6 1.272e+01 -0.881842 1.0481 -0.841332 +#> ds 1 parent 90 6.2 6.085e+00 -0.115212 0.7655 -0.150512 +#> ds 1 parent 90 8.3 6.085e+00 -2.215212 0.7655 -2.893953 +#> ds 1 parent 120 2.2 3.009e+00 0.809439 0.6863 1.179470 +#> ds 1 parent 120 2.4 3.009e+00 0.609439 0.6863 0.888041 +#> ds 1 m1 1 0.3 1.129e+00 0.828817 0.6626 1.250938 +#> ds 1 m1 1 0.2 1.129e+00 0.928817 0.6626 1.401869 +#> ds 1 m1 3 2.2 3.141e+00 0.940880 0.6887 1.366187 +#> ds 1 m1 3 3.0 3.141e+00 0.140880 0.6887 0.204562 +#> ds 1 m1 7 6.5 6.326e+00 -0.174162 0.7735 -0.225175 +#> ds 1 m1 7 5.0 6.326e+00 1.325838 0.7735 1.714181 +#> ds 1 m1 14 10.2 9.883e+00 -0.317417 0.9139 -0.347326 +#> ds 1 m1 14 9.5 9.883e+00 0.382583 0.9139 0.418631 +#> ds 1 m1 28 12.2 1.251e+01 0.309856 1.0378 0.298572 +#> ds 1 m1 28 13.4 1.251e+01 -0.890144 1.0378 -0.857726 +#> ds 1 m1 60 11.8 1.086e+01 -0.940009 0.9584 -0.980812 +#> ds 1 m1 60 13.2 1.086e+01 -2.340009 0.9584 -2.441581 +#> ds 1 m1 90 6.6 7.823e+00 1.222977 0.8278 1.477332 +#> ds 1 m1 90 9.3 7.823e+00 -1.477023 0.8278 -1.784214 +#> ds 1 m1 120 3.5 5.315e+00 1.815201 0.7415 2.447906 +#> ds 1 m1 120 5.4 5.315e+00 -0.084799 0.7415 -0.114356 +#> ds 2 parent 0 118.0 1.031e+02 -14.876736 6.6443 -2.239038 +#> ds 2 parent 0 99.8 1.031e+02 3.323264 6.6443 0.500171 +#> ds 2 parent 1 90.2 9.757e+01 7.371379 6.2902 1.171891 +#> ds 2 parent 1 94.6 9.757e+01 2.971379 6.2902 0.472386 +#> ds 2 parent 3 96.1 8.788e+01 -8.222746 5.6724 -1.449599 +#> ds 2 parent 3 78.4 8.788e+01 9.477254 5.6724 1.670758 +#> ds 2 parent 7 77.9 7.293e+01 -4.972272 4.7218 -1.053054 +#> ds 2 parent 7 77.7 7.293e+01 -4.772272 4.7218 -1.010697 +#> ds 2 parent 14 56.0 5.602e+01 0.016773 3.6513 0.004594 +#> ds 2 parent 14 54.7 5.602e+01 1.316773 3.6513 0.360633 +#> ds 2 parent 28 36.6 3.855e+01 1.945779 2.5575 0.760803 +#> ds 2 parent 28 36.8 3.855e+01 1.745779 2.5575 0.682603 +#> ds 2 parent 60 22.1 2.101e+01 -1.086693 1.4996 -0.724663 +#> ds 2 parent 60 24.7 2.101e+01 -3.686693 1.4996 -2.458475 +#> ds 2 parent 90 12.4 1.246e+01 0.058759 1.0353 0.056757 +#> ds 2 parent 90 10.8 1.246e+01 1.658759 1.0353 1.602256 +#> ds 2 parent 120 6.8 7.406e+00 0.606226 0.8119 0.746659 +#> ds 2 parent 120 7.9 7.406e+00 -0.493774 0.8119 -0.608157 +#> ds 2 m1 1 1.3 1.438e+00 0.138236 0.6650 0.207869 +#> ds 2 m1 3 3.7 3.879e+00 0.178617 0.7040 0.253726 +#> ds 2 m1 3 4.7 3.879e+00 -0.821383 0.7040 -1.166780 +#> ds 2 m1 7 8.1 7.389e+00 -0.710951 0.8113 -0.876337 +#> ds 2 m1 7 7.9 7.389e+00 -0.510951 0.8113 -0.629812 +#> ds 2 m1 14 10.1 1.069e+01 0.593533 0.9507 0.624328 +#> ds 2 m1 14 10.3 1.069e+01 0.393533 0.9507 0.413951 +#> ds 2 m1 28 10.7 1.240e+01 1.703647 1.0325 1.649956 +#> ds 2 m1 28 12.2 1.240e+01 0.203647 1.0325 0.197229 +#> ds 2 m1 60 10.7 1.055e+01 -0.147672 0.9442 -0.156405 +#> ds 2 m1 60 12.5 1.055e+01 -1.947672 0.9442 -2.062848 +#> ds 2 m1 90 9.1 8.010e+00 -1.090041 0.8351 -1.305210 +#> ds 2 m1 90 7.4 8.010e+00 0.609959 0.8351 0.730362 +#> ds 2 m1 120 6.1 5.793e+00 -0.306797 0.7561 -0.405759 +#> ds 2 m1 120 4.5 5.793e+00 1.293203 0.7561 1.710347 +#> ds 3 parent 0 106.2 1.035e+02 -2.712344 6.6675 -0.406801 +#> ds 3 parent 0 106.9 1.035e+02 -3.412344 6.6675 -0.511788 +#> ds 3 parent 1 107.4 9.548e+01 -11.924044 6.1566 -1.936801 +#> ds 3 parent 1 96.1 9.548e+01 -0.624044 6.1566 -0.101362 +#> ds 3 parent 3 79.4 8.246e+01 3.056105 5.3274 0.573662 +#> ds 3 parent 3 82.6 8.246e+01 -0.143895 5.3274 -0.027010 +#> ds 3 parent 7 63.9 6.489e+01 0.991141 4.2122 0.235304 +#> ds 3 parent 7 62.4 6.489e+01 2.491141 4.2122 0.591416 +#> ds 3 parent 14 51.0 4.869e+01 -2.306824 3.1906 -0.723013 +#> ds 3 parent 14 47.1 4.869e+01 1.593176 3.1906 0.499338 +#> ds 3 parent 28 36.1 3.480e+01 -1.304261 2.3260 -0.560722 +#> ds 3 parent 28 36.6 3.480e+01 -1.804261 2.3260 -0.775679 +#> ds 3 parent 60 20.1 1.988e+01 -0.221952 1.4346 -0.154719 +#> ds 3 parent 60 19.8 1.988e+01 0.078048 1.4346 0.054406 +#> ds 3 parent 90 11.3 1.194e+01 0.642458 1.0099 0.636132 +#> ds 3 parent 90 10.7 1.194e+01 1.242458 1.0099 1.230224 +#> ds 3 parent 120 8.2 7.176e+00 -1.023847 0.8034 -1.274423 +#> ds 3 parent 120 7.3 7.176e+00 -0.123847 0.8034 -0.154158 +#> ds 3 m1 0 0.8 8.527e-13 -0.800000 0.6586 -1.214712 +#> ds 3 m1 1 1.8 1.856e+00 0.055925 0.6693 0.083562 +#> ds 3 m1 1 2.3 1.856e+00 -0.444075 0.6693 -0.663537 +#> ds 3 m1 3 4.2 4.780e+00 0.580164 0.7264 0.798676 +#> ds 3 m1 3 4.1 4.780e+00 0.680164 0.7264 0.936340 +#> ds 3 m1 7 6.8 8.410e+00 1.609920 0.8512 1.891455 +#> ds 3 m1 7 10.1 8.410e+00 -1.690080 0.8512 -1.985633 +#> ds 3 m1 14 11.4 1.098e+01 -0.424444 0.9638 -0.440389 +#> ds 3 m1 14 12.8 1.098e+01 -1.824444 0.9638 -1.892979 +#> ds 3 m1 28 11.5 1.142e+01 -0.079336 0.9848 -0.080558 +#> ds 3 m1 28 10.6 1.142e+01 0.820664 0.9848 0.833311 +#> ds 3 m1 60 7.5 9.110e+00 1.610231 0.8803 1.829222 +#> ds 3 m1 60 8.6 9.110e+00 0.510231 0.8803 0.579622 +#> ds 3 m1 90 7.3 6.799e+00 -0.501085 0.7898 -0.634463 +#> ds 3 m1 90 8.1 6.799e+00 -1.301085 0.7898 -1.647404 +#> ds 3 m1 120 5.3 4.868e+00 -0.431505 0.7288 -0.592064 +#> ds 3 m1 120 3.8 4.868e+00 1.068495 0.7288 1.466073 +#> ds 4 parent 0 104.7 9.926e+01 -5.444622 6.3975 -0.851049 +#> ds 4 parent 0 88.3 9.926e+01 10.955378 6.3975 1.712436 +#> ds 4 parent 1 94.2 9.618e+01 1.978413 6.2013 0.319030 +#> ds 4 parent 1 94.6 9.618e+01 1.578413 6.2013 0.254527 +#> ds 4 parent 3 78.1 9.037e+01 12.268550 5.8311 2.103985 +#> ds 4 parent 3 96.5 9.037e+01 -6.131450 5.8311 -1.051508 +#> ds 4 parent 7 76.2 7.999e+01 3.794958 5.1708 0.733918 +#> ds 4 parent 7 77.8 7.999e+01 2.194958 5.1708 0.424489 +#> ds 4 parent 14 70.8 6.518e+01 -5.624996 4.2301 -1.329742 +#> ds 4 parent 14 67.3 6.518e+01 -2.124996 4.2301 -0.502346 +#> ds 4 parent 28 43.1 4.462e+01 1.517860 2.9354 0.517085 +#> ds 4 parent 28 45.1 4.462e+01 -0.482140 2.9354 -0.164249 +#> ds 4 parent 60 21.3 2.130e+01 -0.003305 1.5159 -0.002180 +#> ds 4 parent 60 23.5 2.130e+01 -2.203305 1.5159 -1.453435 +#> ds 4 parent 90 11.8 1.180e+01 0.002834 1.0032 0.002825 +#> ds 4 parent 90 12.1 1.180e+01 -0.297166 1.0032 -0.296226 +#> ds 4 parent 120 7.0 6.868e+00 -0.132251 0.7922 -0.166937 +#> ds 4 parent 120 6.2 6.868e+00 0.667749 0.7922 0.842879 +#> ds 4 m1 0 1.6 0.000e+00 -1.600000 0.6586 -2.429424 +#> ds 4 m1 1 0.9 6.826e-01 -0.217363 0.6600 -0.329315 +#> ds 4 m1 3 3.7 1.935e+00 -1.765082 0.6702 -2.633768 +#> ds 4 m1 3 2.0 1.935e+00 -0.065082 0.6702 -0.097112 +#> ds 4 m1 7 3.6 4.035e+00 0.434805 0.7076 0.614501 +#> ds 4 m1 7 3.8 4.035e+00 0.234805 0.7076 0.331845 +#> ds 4 m1 14 7.1 6.652e+00 -0.448187 0.7846 -0.571220 +#> ds 4 m1 14 6.6 6.652e+00 0.051813 0.7846 0.066036 +#> ds 4 m1 28 9.5 9.156e+00 -0.343805 0.8822 -0.389696 +#> ds 4 m1 28 9.3 9.156e+00 -0.143805 0.8822 -0.163000 +#> ds 4 m1 60 8.3 8.848e+00 0.547762 0.8692 0.630185 +#> ds 4 m1 60 9.0 8.848e+00 -0.152238 0.8692 -0.175146 +#> ds 4 m1 90 6.6 6.674e+00 0.073979 0.7854 0.094194 +#> ds 4 m1 90 7.7 6.674e+00 -1.026021 0.7854 -1.306390 +#> ds 4 m1 120 3.7 4.668e+00 0.967537 0.7234 1.337503 +#> ds 4 m1 120 3.5 4.668e+00 1.167537 0.7234 1.613979 +#> ds 5 parent 0 110.4 1.022e+02 -8.170986 6.5872 -1.240433 +#> ds 5 parent 0 112.1 1.022e+02 -9.870986 6.5872 -1.498509 +#> ds 5 parent 1 93.5 9.513e+01 1.630764 6.1346 0.265832 +#> ds 5 parent 1 91.0 9.513e+01 4.130764 6.1346 0.673359 +#> ds 5 parent 3 71.0 8.296e+01 11.964279 5.3597 2.232268 +#> ds 5 parent 3 89.7 8.296e+01 -6.735721 5.3597 -1.256735 +#> ds 5 parent 7 60.4 6.495e+01 4.547441 4.2157 1.078684 +#> ds 5 parent 7 59.1 6.495e+01 5.847441 4.2157 1.387053 +#> ds 5 parent 14 56.5 4.626e+01 -10.241319 3.0380 -3.371047 +#> ds 5 parent 14 47.0 4.626e+01 -0.741319 3.0380 -0.244014 +#> ds 5 parent 28 30.2 3.026e+01 0.058478 2.0487 0.028544 +#> ds 5 parent 28 23.9 3.026e+01 6.358478 2.0487 3.103661 +#> ds 5 parent 60 17.0 1.792e+01 0.919046 1.3242 0.694024 +#> ds 5 parent 60 18.7 1.792e+01 -0.780954 1.3242 -0.589742 +#> ds 5 parent 90 11.3 1.187e+01 0.573917 1.0066 0.570144 +#> ds 5 parent 90 11.9 1.187e+01 -0.026083 1.0066 -0.025912 +#> ds 5 parent 120 9.0 7.898e+00 -1.102089 0.8307 -1.326622 +#> ds 5 parent 120 8.1 7.898e+00 -0.202089 0.8307 -0.243261 +#> ds 5 m1 0 0.7 -1.421e-14 -0.700000 0.6586 -1.062873 +#> ds 5 m1 1 3.0 3.144e+00 0.143526 0.6887 0.208390 +#> ds 5 m1 1 2.6 3.144e+00 0.543526 0.6887 0.789161 +#> ds 5 m1 3 5.1 8.390e+00 3.290265 0.8504 3.869277 +#> ds 5 m1 3 7.5 8.390e+00 0.890265 0.8504 1.046932 +#> ds 5 m1 7 16.5 1.566e+01 -0.841368 1.2007 -0.700751 +#> ds 5 m1 7 19.0 1.566e+01 -3.341368 1.2007 -2.782928 +#> ds 5 m1 14 22.9 2.188e+01 -1.017753 1.5498 -0.656687 +#> ds 5 m1 14 23.2 2.188e+01 -1.317753 1.5498 -0.850257 +#> ds 5 m1 28 22.2 2.386e+01 1.655914 1.6652 0.994399 +#> ds 5 m1 28 24.4 2.386e+01 -0.544086 1.6652 -0.326731 +#> ds 5 m1 60 15.5 1.859e+01 3.091124 1.3618 2.269915 +#> ds 5 m1 60 19.8 1.859e+01 -1.208876 1.3618 -0.887718 +#> ds 5 m1 90 14.9 1.372e+01 -1.176815 1.0990 -1.070784 +#> ds 5 m1 90 14.2 1.372e+01 -0.476815 1.0990 -0.433854 +#> ds 5 m1 120 10.9 9.961e+00 -0.938796 0.9174 -1.023332 +#> ds 5 m1 120 10.4 9.961e+00 -0.438796 0.9174 -0.478308
    # }
    diff --git a/docs/dev/reference/transform_odeparms.html b/docs/dev/reference/transform_odeparms.html index 6b849d3f..0845d478 100644 --- a/docs/dev/reference/transform_odeparms.html +++ b/docs/dev/reference/transform_odeparms.html @@ -252,7 +252,7 @@ This is no problem for the internal use in mkinfit.# \dontrun{# Compare to the version without transforming rate parametersfit.2<-mkinfit(SFO_SFO, FOCUS_2006_D, transform_rates =FALSE, quiet =TRUE) -
    #> Warning: Observations with value of zero were removed from the data
    #> Error in if (cost < cost.current) { assign("cost.current", cost, inherits = TRUE) if (!quiet) cat(ifelse(OLS, "Sum of squared residuals", "Negative log-likelihood"), " at call ", calls, ": ", signif(cost.current, 6), "\n", sep = "")}: missing value where TRUE/FALSE needed
    #> Timing stopped at: 0.003 0 0.002
    fit.2.s <- summary(fit.2) +
    #> Warning: Observations with value of zero were removed from the data
    #> Error in if (cost < cost.current) { assign("cost.current", cost, inherits = TRUE) if (!quiet) cat(ifelse(OLS, "Sum of squared residuals", "Negative log-likelihood"), " at call ", calls, ": ", signif(cost.current, 6), "\n", sep = "")}: missing value where TRUE/FALSE needed
    #> Timing stopped at: 0.002 0 0.003
    fit.2.s <- summary(fit.2)
    #> Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'summary': object 'fit.2' not found
    print(fit.2.s$par, 3)
    #> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'print': object 'fit.2.s' not found
    print(fit.2.s$bpar, 3)
    #> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'print': object 'fit.2.s' not found
    # } -- cgit v1.2.1