From bc3825ae2d12c18ea3d3caf17eb23c93fef180b8 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 8 Oct 2020 09:31:35 +0200 Subject: Fix issues for release --- docs/dev/reference/nlme.mmkin.html | 97 +++++++++++++++++++------------------- 1 file changed, 48 insertions(+), 49 deletions(-) (limited to 'docs/dev/reference/nlme.mmkin.html') diff --git a/docs/dev/reference/nlme.mmkin.html b/docs/dev/reference/nlme.mmkin.html index c7db9c23..16df54af 100644 --- a/docs/dev/reference/nlme.mmkin.html +++ b/docs/dev/reference/nlme.mmkin.html @@ -262,45 +262,44 @@ with additional elements

Examples

ds <- lapply(experimental_data_for_UBA_2019[6:10],
  function(x) subset(x$data[c("name", "time", "value")], name == "parent"))
-f <- mmkin("SFO", ds, quiet = TRUE, cores = 1)
-library(nlme)
+f <- mmkin("SFO", ds, quiet = TRUE, cores = 1)
#> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0195
#> Warning: Shapiro-Wilk test for standardized residuals: p =  0.011
library(nlme)
 endpoints(f[[1]])
#> $distimes
 #>            DT50     DT90
 #> parent 11.96183 39.73634
 #> 
f_nlme <- nlme(f)
 print(f_nlme)
#> Nonlinear mixed-effects model fit by maximum likelihood
-#>   Model: value ~ (mkin::get_deg_func())(name, time, parent_0, log_k_parent_sink) 
+#>   Model: value ~ (mkin::get_deg_func())(name, time, parent_0, log_k_parent) 
 #>   Data: "Not shown" 
 #>   Log-likelihood: -307.5269
-#>   Fixed: list(parent_0 ~ 1, log_k_parent_sink ~ 1) 
-#>          parent_0 log_k_parent_sink 
-#>         85.540979         -3.229602 
+#>   Fixed: list(parent_0 ~ 1, log_k_parent ~ 1) 
+#>     parent_0 log_k_parent 
+#>    85.541149    -3.229596 
 #> 
 #> Random effects:
-#>  Formula: list(parent_0 ~ 1, log_k_parent_sink ~ 1)
+#>  Formula: list(parent_0 ~ 1, log_k_parent ~ 1)
 #>  Level: ds
 #>  Structure: Diagonal
-#>         parent_0 log_k_parent_sink Residual
-#> StdDev: 1.308245          1.288586 6.304923
+#>         parent_0 log_k_parent Residual
+#> StdDev:  1.30857     1.288591 6.304906
 #> 
 #> Number of Observations: 90
 #> Number of Groups: 5 
endpoints(f_nlme)
#> $distimes
 #>            DT50     DT90
-#> parent 17.51556 58.18543
+#> parent 17.51545 58.18505
 #> 
# \dontrun{
   f_nlme_2 <- nlme(f, start = c(parent_0 = 100, log_k_parent_sink = 0.1))
   update(f_nlme_2, random = parent_0 ~ 1)
#> Nonlinear mixed-effects model fit by maximum likelihood
-#>   Model: value ~ (mkin::get_deg_func())(name, time, parent_0, log_k_parent_sink) 
+#>   Model: value ~ (mkin::get_deg_func())(name, time, parent_0, log_k_parent) 
 #>   Data: "Not shown" 
 #>   Log-likelihood: -404.3729
-#>   Fixed: list(parent_0 ~ 1, log_k_parent_sink ~ 1) 
-#>          parent_0 log_k_parent_sink 
-#>         75.933480         -3.555983 
+#>   Fixed: list(parent_0 ~ 1, log_k_parent ~ 1) 
+#>     parent_0 log_k_parent 
+#>    75.933480    -3.555983 
 #> 
 #> Random effects:
 #>  Formula: parent_0 ~ 1 | ds
 #>            parent_0 Residual
-#> StdDev: 0.002416802 21.63027
+#> StdDev: 0.002416792 21.63027
 #> 
 #> Number of Observations: 90
 #> Number of Groups: 5 
  # Test on some real data
@@ -332,88 +331,88 @@ with additional elements

   f_nlme_fomc_sfo <- nlme(f_2["FOMC-SFO", ],
     control = list(pnlsMaxIter = 100, tolerance = 1e-4), verbose = TRUE)
#> 
 #> **Iteration 1
-#> LME step: Loglik: -394.1603, nlminb iterations: 2
+#> LME step: Loglik: -394.1603, nlminb iterations: 3
 #> reStruct  parameters:
 #>        ds1        ds2        ds3        ds4        ds5 
-#> -0.2079863  0.8563823  1.7454253  1.0917707  1.2756955 
+#> -0.2079793  0.8563830  1.7454105  1.0917354  1.2756825 
 #>  Beginning PNLS step: ..  completed fit_nlme() step.
-#> PNLS step: RSS =  643.8814 
-#>  fixed effects: 94.17379  -5.473189  -0.6970234  -0.202509  2.103883  
+#> PNLS step: RSS =  643.8803 
+#>  fixed effects: 94.17379  -5.473193  -0.6970236  -0.2025091  2.103883  
 #>  iterations: 100 
 #> Convergence crit. (must all become <= tolerance = 0.0001):
 #>     fixed  reStruct 
-#> 0.7959873 0.1447512 
+#> 0.7960134 0.1447728 
 #> 
 #> **Iteration 2
 #> LME step: Loglik: -396.3824, nlminb iterations: 7
 #> reStruct  parameters:
 #>           ds1           ds2           ds3           ds4           ds5 
-#> -1.712406e-01 -2.278541e-05  1.842120e+00  1.073975e+00  1.322924e+00 
+#> -1.712404e-01 -2.432655e-05  1.842120e+00  1.073975e+00  1.322925e+00 
 #>  Beginning PNLS step: ..  completed fit_nlme() step.
-#> PNLS step: RSS =  643.8025 
-#>  fixed effects: 94.17385  -5.473491  -0.6970406  -0.2025139  2.103871  
+#> PNLS step: RSS =  643.8035 
+#>  fixed effects: 94.17385  -5.473487  -0.6970404  -0.2025137  2.103871  
 #>  iterations: 100 
 #> Convergence crit. (must all become <= tolerance = 0.0001):
-#>       fixed    reStruct 
-#> 5.51758e-05 1.26861e-03 
+#>        fixed     reStruct 
+#> 5.382757e-05 1.236667e-03 
 #> 
 #> **Iteration 3
 #> LME step: Loglik: -396.3825, nlminb iterations: 7
 #> reStruct  parameters:
 #>           ds1           ds2           ds3           ds4           ds5 
-#> -0.1712500923 -0.0001515734  1.8420972550  1.0739796967  1.3229177241 
+#> -0.1712499044 -0.0001499831  1.8420971364  1.0739799123  1.3229167796 
 #>  Beginning PNLS step: ..  completed fit_nlme() step.
-#> PNLS step: RSS =  643.7941 
-#>  fixed effects: 94.17386  -5.473523  -0.6970424  -0.2025146  2.103869  
+#> PNLS step: RSS =  643.7948 
+#>  fixed effects: 94.17386  -5.473521  -0.6970422  -0.2025144  2.10387  
 #>  iterations: 100 
 #> Convergence crit. (must all become <= tolerance = 0.0001):
 #>        fixed     reStruct 
-#> 5.792621e-06 1.335434e-04 
+#> 6.072817e-06 1.400857e-04 
 #> 
 #> **Iteration 4
 #> LME step: Loglik: -396.3825, nlminb iterations: 7
 #> reStruct  parameters:
 #>           ds1           ds2           ds3           ds4           ds5 
-#> -0.1712517206 -0.0001651603  1.8420950864  1.0739800294  1.3229173529 
+#> -0.1712529502 -0.0001641277  1.8420957542  1.0739797181  1.3229173076 
 #>  Beginning PNLS step: ..  completed fit_nlme() step.
-#> PNLS step: RSS =  643.7949 
-#>  fixed effects: 94.17386  -5.473521  -0.6970423  -0.2025145  2.10387  
+#> PNLS step: RSS =  643.7936 
+#>  fixed effects: 94.17386  -5.473526  -0.6970426  -0.2025146  2.103869  
 #>  iterations: 100 
 #> Convergence crit. (must all become <= tolerance = 0.0001):
 #>        fixed     reStruct 
-#> 4.025781e-07 9.628656e-06 
  f_nlme_dfop_sfo <- nlme(f_2["DFOP-SFO", ],
+#> 1.027451e-06 2.275704e-05 
  f_nlme_dfop_sfo <- nlme(f_2["DFOP-SFO", ],
     control = list(pnlsMaxIter = 120, tolerance = 5e-4), verbose = TRUE)
#> 
 #> **Iteration 1
-#> LME step: Loglik: -404.9583, nlminb iterations: 1
+#> LME step: Loglik: -404.9582, nlminb iterations: 1
 #> reStruct  parameters:
 #>        ds1        ds2        ds3        ds4        ds5        ds6 
-#> -0.4114357  0.9798641  1.6990035  0.7293314  0.3354323  1.7113047 
+#> -0.4114355  0.9798697  1.6990037  0.7293315  0.3354323  1.7113046 
 #>  Beginning PNLS step: ..  completed fit_nlme() step.
-#> PNLS step: RSS =  630.3642 
-#>  fixed effects: 93.82269  -5.455991  -0.6788957  -1.862196  -4.199671  0.0553284  
+#> PNLS step: RSS =  630.3644 
+#>  fixed effects: 93.82269  -5.455991  -0.6788957  -1.862196  -4.199671  0.05532828  
 #>  iterations: 120 
 #> Convergence crit. (must all become <= tolerance = 0.0005):
 #>     fixed  reStruct 
-#> 0.7879730 0.5822574 
+#> 0.7885368 0.5822683 
 #> 
 #> **Iteration 2
 #> LME step: Loglik: -407.7755, nlminb iterations: 11
 #> reStruct  parameters:
 #>          ds1          ds2          ds3          ds4          ds5          ds6 
-#> -0.371224105  0.003056163  1.789939431  0.724671132  0.301602942  1.754200482 
+#> -0.371224133  0.003056179  1.789939402  0.724671158  0.301602977  1.754200729 
 #>  Beginning PNLS step: ..  completed fit_nlme() step.
-#> PNLS step: RSS =  630.364 
-#>  fixed effects: 93.82269  -5.455991  -0.6788958  -1.862196  -4.199671  0.05532834  
+#> PNLS step: RSS =  630.3633 
+#>  fixed effects: 93.82269  -5.455992  -0.6788958  -1.862196  -4.199671  0.05532831  
 #>  iterations: 120 
 #> Convergence crit. (must all become <= tolerance = 0.0005):
 #>        fixed     reStruct 
-#> 9.814652e-07 1.059239e-05 
  plot(f_2["FOMC-SFO", 3:4])
  plot(f_nlme_fomc_sfo, 3:4)

+#> 4.789774e-07 2.200661e-05 
  plot(f_2["FOMC-SFO", 3:4])
  plot(f_nlme_fomc_sfo, 3:4)

   plot(f_2["DFOP-SFO", 3:4])
  plot(f_nlme_dfop_sfo, 3:4)

   anova(f_nlme_dfop_sfo, f_nlme_fomc_sfo, f_nlme_sfo_sfo)
#>                 Model df       AIC       BIC    logLik   Test   L.Ratio p-value
-#> f_nlme_dfop_sfo     1 13  843.8547  884.6201 -408.9274                         
-#> f_nlme_fomc_sfo     2 11  818.5151  853.0089 -398.2576 1 vs 2  21.33957  <.0001
-#> f_nlme_sfo_sfo      3  9 1085.1821 1113.4043 -533.5910 2 vs 3 270.66697  <.0001
  anova(f_nlme_dfop_sfo, f_nlme_sfo_sfo) # if we ignore FOMC
#>                 Model df       AIC       BIC    logLik   Test  L.Ratio p-value
-#> f_nlme_dfop_sfo     1 13  843.8547  884.6201 -408.9274                        
+#> f_nlme_dfop_sfo     1 13  843.8547  884.6201 -408.9273                         
+#> f_nlme_fomc_sfo     2 11  818.5149  853.0087 -398.2575 1 vs 2  21.33975  <.0001
+#> f_nlme_sfo_sfo      3  9 1085.1821 1113.4043 -533.5910 2 vs 3 270.66716  <.0001
  anova(f_nlme_dfop_sfo, f_nlme_sfo_sfo) # if we ignore FOMC
#>                 Model df       AIC       BIC    logLik   Test  L.Ratio p-value
+#> f_nlme_dfop_sfo     1 13  843.8547  884.6201 -408.9273                        
 #> f_nlme_sfo_sfo      2  9 1085.1821 1113.4043 -533.5910 1 vs 2 249.3274  <.0001

   endpoints(f_nlme_sfo_sfo)
#> $ff
 #> parent_sink   parent_A1     A1_sink 
@@ -428,9 +427,9 @@ with additional elements

 #>   0.2768574   0.7231426 
 #> 
 #> $distimes
-#>             DT50     DT90  DT50_k1  DT50_k2
-#> parent  11.07091 104.6320 4.462384 46.20825
-#> A1     162.30518 539.1661       NA       NA
+#>             DT50     DT90 DT50back  DT50_k1  DT50_k2
+#> parent  11.07091 104.6320 31.49738 4.462384 46.20825
+#> A1     162.30536 539.1667       NA       NA       NA
 #> 
# }
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