From 6653ff2507f45eae909f491a9af3f1eb5358a600 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 1 Mar 2018 14:32:46 +0100 Subject: Static documentation rebuilt using current pkgdown::build_site() --- docs/reference/mkinfit.html | 859 +++----------------------------------------- 1 file changed, 52 insertions(+), 807 deletions(-) (limited to 'docs/reference/mkinfit.html') diff --git a/docs/reference/mkinfit.html b/docs/reference/mkinfit.html index 0102aecb..4fb5ef9a 100644 --- a/docs/reference/mkinfit.html +++ b/docs/reference/mkinfit.html @@ -18,12 +18,29 @@ + + + + + + + @@ -395,17 +412,17 @@

Examples

# Use shorthand notation for parent only degradation
 fit <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
-summary(fit)
#> mkin version:    0.9.47.1 
-#> R version:       3.4.3 
-#> Date of fit:     Tue Jan 30 10:05:48 2018 
-#> Date of summary: Tue Jan 30 10:05:48 2018 
+summary(fit)
#> mkin version used for fitting:    0.9.47.1 
+#> R version used for fitting:       3.4.3 
+#> Date of fit:     Thu Mar  1 14:26:18 2018 
+#> Date of summary: Thu Mar  1 14:26:18 2018 
 #> 
 #> Equations:
 #> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 #> 
 #> Model predictions using solution type analytical 
 #> 
-#> Fitted with method Port using 64 model solutions performed in 0.31 s
+#> Fitted with method Port using 64 model solutions performed in 0.135 s
 #> 
 #> Weighting: none
 #> 
@@ -474,7 +491,7 @@
   m1 = mkinsub("SFO"))
#> Successfully compiled differential equation model from auto-generated C code.
# Fit the model to the FOCUS example dataset D using defaults
 print(system.time(fit <- mkinfit(SFO_SFO, FOCUS_2006_D,
                            solution_type = "eigen", quiet = TRUE)))
#>    user  system elapsed 
-#>   1.196   0.000   1.195 
coef(fit)
#>          parent_0 log_k_parent_sink   log_k_parent_m1     log_k_m1_sink 
+#>    0.84    0.00    0.84 
coef(fit)
#>          parent_0 log_k_parent_sink   log_k_parent_m1     log_k_m1_sink 
 #>          99.59848          -3.03822          -2.98030          -5.24750 
endpoints(fit)
#> $ff
 #> parent_sink   parent_m1     m1_sink 
 #>    0.485524    0.514476    1.000000 
@@ -486,92 +503,19 @@
 #>              DT50      DT90
 #> parent   7.022929  23.32967
 #> m1     131.760712 437.69961
-#> 

+#> 
# NOT RUN {
 # deSolve is slower when no C compiler (gcc) was available during model generation
 print(system.time(fit.deSolve <- mkinfit(SFO_SFO, FOCUS_2006_D,
-                           solution_type = "deSolve")))
#> Model cost at call  1 :  18915.53 
-#> Model cost at call  2 :  18915.53 
-#> Model cost at call  6 :  11424.02 
-#> Model cost at call  10 :  11424 
-#> Model cost at call  12 :  4094.396 
-#> Model cost at call  16 :  4094.396 
-#> Model cost at call  19 :  1340.595 
-#> Model cost at call  20 :  1340.593 
-#> Model cost at call  25 :  1072.239 
-#> Model cost at call  28 :  1072.236 
-#> Model cost at call  30 :  874.2614 
-#> Model cost at call  33 :  874.2611 
-#> Model cost at call  35 :  616.2379 
-#> Model cost at call  37 :  616.2374 
-#> Model cost at call  40 :  467.4387 
-#> Model cost at call  42 :  467.4382 
-#> Model cost at call  46 :  398.2913 
-#> Model cost at call  48 :  398.2912 
-#> Model cost at call  49 :  398.2911 
-#> Model cost at call  51 :  395.0711 
-#> Model cost at call  54 :  395.071 
-#> Model cost at call  56 :  378.3298 
-#> Model cost at call  59 :  378.3298 
-#> Model cost at call  62 :  376.9812 
-#> Model cost at call  64 :  376.9811 
-#> Model cost at call  67 :  375.2085 
-#> Model cost at call  69 :  375.2085 
-#> Model cost at call  70 :  375.2085 
-#> Model cost at call  71 :  375.2085 
-#> Model cost at call  72 :  374.5723 
-#> Model cost at call  74 :  374.5723 
-#> Model cost at call  77 :  374.0075 
-#> Model cost at call  79 :  374.0075 
-#> Model cost at call  80 :  374.0075 
-#> Model cost at call  82 :  373.1711 
-#> Model cost at call  84 :  373.1711 
-#> Model cost at call  87 :  372.6445 
-#> Model cost at call  88 :  372.1614 
-#> Model cost at call  90 :  372.1614 
-#> Model cost at call  91 :  372.1614 
-#> Model cost at call  94 :  371.6464 
-#> Model cost at call  99 :  371.4299 
-#> Model cost at call  101 :  371.4299 
-#> Model cost at call  104 :  371.4071 
-#> Model cost at call  106 :  371.4071 
-#> Model cost at call  107 :  371.4071 
-#> Model cost at call  109 :  371.2524 
-#> Model cost at call  113 :  371.2524 
-#> Model cost at call  114 :  371.2136 
-#> Model cost at call  115 :  371.2136 
-#> Model cost at call  116 :  371.2136 
-#> Model cost at call  119 :  371.2134 
-#> Model cost at call  120 :  371.2134 
-#> Model cost at call  122 :  371.2134 
-#> Model cost at call  123 :  371.2134 
-#> Model cost at call  125 :  371.2134 
-#> Model cost at call  126 :  371.2134 
-#> Model cost at call  135 :  371.2134 
-#> Model cost at call  147 :  371.2134 
-#> Model cost at call  151 :  371.2134 
-#> Model cost at call  152 :  371.2134 
-#> Model cost at call  153 :  371.2134 
-#> Optimisation by method Port successfully terminated.
-#>    user  system elapsed 
-#>   1.008   0.000   1.006 
coef(fit.deSolve)
#>          parent_0 log_k_parent_sink   log_k_parent_m1     log_k_m1_sink 
-#>          99.59848          -3.03822          -2.98030          -5.24750 
endpoints(fit.deSolve)
#> $ff
-#> parent_sink   parent_m1     m1_sink 
-#>    0.485524    0.514476    1.000000 
-#> 
-#> $SFORB
-#> logical(0)
-#> 
-#> $distimes
-#>              DT50      DT90
-#> parent   7.022929  23.32967
-#> m1     131.760712 437.69961
-#> 

-
-# Use stepwise fitting, using optimised parameters from parent only fit, FOMC
-
+                           solution_type = "deSolve")))
+coef(fit.deSolve)
+endpoints(fit.deSolve)
+# }

+# Use stepwise fitting, using optimised parameters from parent only fit, FOMC
+
# NOT RUN {
 FOMC_SFO <- mkinmod(
   parent = mkinsub("FOMC", "m1"),
-  m1 = mkinsub("SFO"))
#> Successfully compiled differential equation model from auto-generated C code.
# Fit the model to the FOCUS example dataset D using defaults
+  m1 = mkinsub("SFO"))
+# Fit the model to the FOCUS example dataset D using defaults
 fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE)
 # Use starting parameters from parent only FOMC fit
 fit.FOMC = mkinfit("FOMC", FOCUS_2006_D, quiet = TRUE)
@@ -581,739 +525,40 @@
 # Use stepwise fitting, using optimised parameters from parent only fit, SFORB
 SFORB_SFO <- mkinmod(
   parent = list(type = "SFORB", to = "m1", sink = TRUE),
-  m1 = list(type = "SFO"))
#> Successfully compiled differential equation model from auto-generated C code.
# Fit the model to the FOCUS example dataset D using defaults
+  m1 = list(type = "SFO"))
+# Fit the model to the FOCUS example dataset D using defaults
 fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D, quiet = TRUE)
 fit.SFORB_SFO.deSolve <- mkinfit(SFORB_SFO, FOCUS_2006_D, solution_type = "deSolve",
                                  quiet = TRUE)
 # Use starting parameters from parent only SFORB fit (not really needed in this case)
 fit.SFORB = mkinfit("SFORB", FOCUS_2006_D, quiet = TRUE)
 fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D, parms.ini = fit.SFORB$bparms.ode, quiet = TRUE)
-
-
-
+# }

+
# NOT RUN {
 # Weighted fits, including IRLS
 SFO_SFO.ff <- mkinmod(parent = mkinsub("SFO", "m1"),
-                      m1 = mkinsub("SFO"), use_of_ff = "max")
#> Successfully compiled differential equation model from auto-generated C code.
f.noweight <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE)
-summary(f.noweight)
#> mkin version:    0.9.47.1 
-#> R version:       3.4.3 
-#> Date of fit:     Tue Jan 30 10:06:00 2018 
-#> Date of summary: Tue Jan 30 10:06:00 2018 
-#> 
-#> Equations:
-#> d_parent/dt = - k_parent * parent
-#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1
-#> 
-#> Model predictions using solution type deSolve 
-#> 
-#> Fitted with method Port using 185 model solutions performed in 0.739 s
-#> 
-#> Weighting: none
-#> 
-#> Starting values for parameters to be optimised:
-#>                   value   type
-#> parent_0       100.7500  state
-#> k_parent         0.1000 deparm
-#> k_m1             0.1001 deparm
-#> f_parent_to_m1   0.5000 deparm
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>                     value lower upper
-#> parent_0       100.750000  -Inf   Inf
-#> log_k_parent    -2.302585  -Inf   Inf
-#> log_k_m1        -2.301586  -Inf   Inf
-#> f_parent_ilr_1   0.000000  -Inf   Inf
-#> 
-#> Fixed parameter values:
-#>      value  type
-#> m1_0     0 state
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>                Estimate Std. Error   Lower    Upper
-#> parent_0       99.60000    1.61400 96.3300 102.9000
-#> log_k_parent   -2.31600    0.04187 -2.4010  -2.2310
-#> log_k_m1       -5.24800    0.13610 -5.5230  -4.9720
-#> f_parent_ilr_1  0.04096    0.06477 -0.0904   0.1723
-#> 
-#> Parameter correlation:
-#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1
-#> parent_0         1.0000       0.5178  -0.1701        -0.5489
-#> log_k_parent     0.5178       1.0000  -0.3285        -0.5451
-#> log_k_m1        -0.1701      -0.3285   1.0000         0.7466
-#> f_parent_ilr_1  -0.5489      -0.5451   0.7466         1.0000
-#> 
-#> Residual standard error: 3.211 on 36 degrees of freedom
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>                 Estimate t value    Pr(>t)     Lower     Upper
-#> parent_0       99.600000  61.720 2.024e-38 96.330000 1.029e+02
-#> k_parent        0.098700  23.880 5.701e-24  0.090660 1.074e-01
-#> k_m1            0.005261   7.349 5.758e-09  0.003992 6.933e-03
-#> f_parent_to_m1  0.514500  22.490 4.374e-23  0.468100 5.606e-01
-#> 
-#> Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data   6.398       4 15
-#> parent     6.459       2  7
-#> m1         4.690       2  8
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_m1   0.5145
-#> parent_sink 0.4855
-#> 
-#> Estimated disappearance times:
-#>           DT50   DT90
-#> parent   7.023  23.33
-#> m1     131.761 437.70
-#> 
-#> Data:
-#>  time variable observed predicted   residual
-#>     0   parent    99.46  99.59848 -1.385e-01
-#>     0   parent   102.04  99.59848  2.442e+00
-#>     1   parent    93.50  90.23787  3.262e+00
-#>     1   parent    92.50  90.23787  2.262e+00
-#>     3   parent    63.23  74.07319 -1.084e+01
-#>     3   parent    68.99  74.07319 -5.083e+00
-#>     7   parent    52.32  49.91206  2.408e+00
-#>     7   parent    55.13  49.91206  5.218e+00
-#>    14   parent    27.27  25.01257  2.257e+00
-#>    14   parent    26.64  25.01257  1.627e+00
-#>    21   parent    11.50  12.53462 -1.035e+00
-#>    21   parent    11.64  12.53462 -8.946e-01
-#>    35   parent     2.85   3.14787 -2.979e-01
-#>    35   parent     2.91   3.14787 -2.379e-01
-#>    50   parent     0.69   0.71624 -2.624e-02
-#>    50   parent     0.63   0.71624 -8.624e-02
-#>    75   parent     0.05   0.06074 -1.074e-02
-#>    75   parent     0.06   0.06074 -7.381e-04
-#>     0       m1     0.00   0.00000  0.000e+00
-#>     0       m1     0.00   0.00000  0.000e+00
-#>     1       m1     4.84   4.80296  3.704e-02
-#>     1       m1     5.64   4.80296  8.370e-01
-#>     3       m1    12.91  13.02400 -1.140e-01
-#>     3       m1    12.96  13.02400 -6.400e-02
-#>     7       m1    22.97  25.04476 -2.075e+00
-#>     7       m1    24.47  25.04476 -5.748e-01
-#>    14       m1    41.69  36.69002  5.000e+00
-#>    14       m1    33.21  36.69002 -3.480e+00
-#>    21       m1    44.37  41.65310  2.717e+00
-#>    21       m1    46.44  41.65310  4.787e+00
-#>    35       m1    41.22  43.31312 -2.093e+00
-#>    35       m1    37.95  43.31312 -5.363e+00
-#>    50       m1    41.19  41.21831 -2.831e-02
-#>    50       m1    40.01  41.21831 -1.208e+00
-#>    75       m1    40.09  36.44703  3.643e+00
-#>    75       m1    33.85  36.44703 -2.597e+00
-#>   100       m1    31.04  31.98163 -9.416e-01
-#>   100       m1    33.13  31.98163  1.148e+00
-#>   120       m1    25.15  28.78984 -3.640e+00
-#>   120       m1    33.31  28.78984  4.520e+00
f.irls <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, reweight.method = "obs", quiet = TRUE)
-summary(f.irls)
#> mkin version:    0.9.47.1 
-#> R version:       3.4.3 
-#> Date of fit:     Tue Jan 30 10:06:02 2018 
-#> Date of summary: Tue Jan 30 10:06:02 2018 
-#> 
-#> Equations:
-#> d_parent/dt = - k_parent * parent
-#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1
-#> 
-#> Model predictions using solution type deSolve 
-#> 
-#> Fitted with method Port using 523 model solutions performed in 2.151 s
-#> 
-#> Weighting: none
-#> 
-#> Iterative reweighting with method obs 
-#> Final mean squared residuals of observed variables:
-#>    parent        m1 
-#> 11.573408  7.407845 
-#> 
-#> Starting values for parameters to be optimised:
-#>                   value   type
-#> parent_0       100.7500  state
-#> k_parent         0.1000 deparm
-#> k_m1             0.1001 deparm
-#> f_parent_to_m1   0.5000 deparm
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>                     value lower upper
-#> parent_0       100.750000  -Inf   Inf
-#> log_k_parent    -2.302585  -Inf   Inf
-#> log_k_m1        -2.301586  -Inf   Inf
-#> f_parent_ilr_1   0.000000  -Inf   Inf
-#> 
-#> Fixed parameter values:
-#>      value  type
-#> m1_0     0 state
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>                Estimate Std. Error    Lower   Upper
-#> parent_0       99.67000    1.79200 96.04000 103.300
-#> log_k_parent   -2.31200    0.04560 -2.40400  -2.219
-#> log_k_m1       -5.25100    0.12510 -5.50500  -4.998
-#> f_parent_ilr_1  0.03785    0.06318 -0.09027   0.166
-#> 
-#> Parameter correlation:
-#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1
-#> parent_0         1.0000       0.5083  -0.1979        -0.6148
-#> log_k_parent     0.5083       1.0000  -0.3894        -0.6062
-#> log_k_m1        -0.1979      -0.3894   1.0000         0.7417
-#> f_parent_ilr_1  -0.6148      -0.6062   0.7417         1.0000
-#> 
-#> Residual standard error: 1.054 on 36 degrees of freedom
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>                Estimate t value    Pr(>t)     Lower     Upper
-#> parent_0       99.67000  55.630 8.184e-37 96.040000 1.033e+02
-#> k_parent        0.09906  21.930 1.016e-22  0.090310 1.087e-01
-#> k_m1            0.00524   7.996 8.486e-10  0.004066 6.753e-03
-#> f_parent_to_m1  0.51340  23.000 2.038e-23  0.468100 5.584e-01
-#> 
-#> Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data   6.399       4 15
-#> parent     6.466       2  7
-#> m1         4.679       2  8
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_m1   0.5134
-#> parent_sink 0.4866
-#> 
-#> Estimated disappearance times:
-#>           DT50   DT90
-#> parent   6.997  23.24
-#> m1     132.282 439.43
-#> 
-#> Data:
-#>  time variable observed predicted   residual   err
-#>     0   parent    99.46  99.67218 -2.122e-01 3.402
-#>     0   parent   102.04  99.67218  2.368e+00 3.402
-#>     1   parent    93.50  90.27153  3.228e+00 3.402
-#>     1   parent    92.50  90.27153  2.228e+00 3.402
-#>     3   parent    63.23  74.04648 -1.082e+01 3.402
-#>     3   parent    68.99  74.04648 -5.056e+00 3.402
-#>     7   parent    52.32  49.82092  2.499e+00 3.402
-#>     7   parent    55.13  49.82092  5.309e+00 3.402
-#>    14   parent    27.27  24.90287  2.367e+00 3.402
-#>    14   parent    26.64  24.90287  1.737e+00 3.402
-#>    21   parent    11.50  12.44764 -9.476e-01 3.402
-#>    21   parent    11.64  12.44764 -8.076e-01 3.402
-#>    35   parent     2.85   3.11002 -2.600e-01 3.402
-#>    35   parent     2.91   3.11002 -2.000e-01 3.402
-#>    50   parent     0.69   0.70374 -1.374e-02 3.402
-#>    50   parent     0.63   0.70374 -7.374e-02 3.402
-#>    75   parent     0.05   0.05913 -9.134e-03 3.402
-#>    75   parent     0.06   0.05913  8.662e-04 3.402
-#>     0       m1     0.00   0.00000  0.000e+00 2.722
-#>     0       m1     0.00   0.00000  0.000e+00 2.722
-#>     1       m1     4.84   4.81328  2.672e-02 2.722
-#>     1       m1     5.64   4.81328  8.267e-01 2.722
-#>     3       m1    12.91  13.04779 -1.378e-01 2.722
-#>     3       m1    12.96  13.04779 -8.779e-02 2.722
-#>     7       m1    22.97  25.07615 -2.106e+00 2.722
-#>     7       m1    24.47  25.07615 -6.062e-01 2.722
-#>    14       m1    41.69  36.70729  4.983e+00 2.722
-#>    14       m1    33.21  36.70729 -3.497e+00 2.722
-#>    21       m1    44.37  41.65050  2.720e+00 2.722
-#>    21       m1    46.44  41.65050  4.790e+00 2.722
-#>    35       m1    41.22  43.28866 -2.069e+00 2.722
-#>    35       m1    37.95  43.28866 -5.339e+00 2.722
-#>    50       m1    41.19  41.19338 -3.383e-03 2.722
-#>    50       m1    40.01  41.19338 -1.183e+00 2.722
-#>    75       m1    40.09  36.43820  3.652e+00 2.722
-#>    75       m1    33.85  36.43820 -2.588e+00 2.722
-#>   100       m1    31.04  31.98971 -9.497e-01 2.722
-#>   100       m1    33.13  31.98971  1.140e+00 2.722
-#>   120       m1    25.15  28.80897 -3.659e+00 2.722
-#>   120       m1    33.31  28.80897  4.501e+00 2.722
f.w.mean <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, weight = "mean", quiet = TRUE)
-summary(f.w.mean)
#> mkin version:    0.9.47.1 
-#> R version:       3.4.3 
-#> Date of fit:     Tue Jan 30 10:06:03 2018 
-#> Date of summary: Tue Jan 30 10:06:03 2018 
-#> 
-#> Equations:
-#> d_parent/dt = - k_parent * parent
-#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1
-#> 
-#> Model predictions using solution type deSolve 
-#> 
-#> Fitted with method Port using 155 model solutions performed in 0.675 s
-#> 
-#> Weighting: mean
-#> 
-#> Starting values for parameters to be optimised:
-#>                   value   type
-#> parent_0       100.7500  state
-#> k_parent         0.1000 deparm
-#> k_m1             0.1001 deparm
-#> f_parent_to_m1   0.5000 deparm
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>                     value lower upper
-#> parent_0       100.750000  -Inf   Inf
-#> log_k_parent    -2.302585  -Inf   Inf
-#> log_k_m1        -2.301586  -Inf   Inf
-#> f_parent_ilr_1   0.000000  -Inf   Inf
-#> 
-#> Fixed parameter values:
-#>      value  type
-#> m1_0     0 state
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>                Estimate Std. Error    Lower    Upper
-#> parent_0        99.7300    1.93200 95.81000 103.6000
-#> log_k_parent    -2.3090    0.04837 -2.40700  -2.2110
-#> log_k_m1        -5.2550    0.12070 -5.49900  -5.0100
-#> f_parent_ilr_1   0.0354    0.06344 -0.09327   0.1641
-#> 
-#> Parameter correlation:
-#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1
-#> parent_0         1.0000       0.5004  -0.2143        -0.6514
-#> log_k_parent     0.5004       1.0000  -0.4282        -0.6383
-#> log_k_m1        -0.2143      -0.4282   1.0000         0.7390
-#> f_parent_ilr_1  -0.6514      -0.6383   0.7390         1.0000
-#> 
-#> Residual standard error: 0.09829 on 36 degrees of freedom
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>                 Estimate t value    Pr(>t)    Lower     Upper
-#> parent_0       99.730000  51.630 1.166e-35 95.81000 1.036e+02
-#> k_parent        0.099360  20.670 7.303e-22  0.09007 1.096e-01
-#> k_m1            0.005224   8.287 3.649e-10  0.00409 6.672e-03
-#> f_parent_to_m1  0.512500  22.860 2.497e-23  0.46710 5.578e-01
-#> 
-#> Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data   6.401       4 15
-#> parent     6.473       2  7
-#> m1         4.671       2  8
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_m1   0.5125
-#> parent_sink 0.4875
-#> 
-#> Estimated disappearance times:
-#>           DT50   DT90
-#> parent   6.976  23.18
-#> m1     132.696 440.81
-#> 
-#> Data:
-#>  time variable observed predicted   residual
-#>     0   parent    99.46  99.73057  -0.270570
-#>     0   parent   102.04  99.73057   2.309430
-#>     1   parent    93.50  90.29805   3.201945
-#>     1   parent    92.50  90.29805   2.201945
-#>     3   parent    63.23  74.02503 -10.795028
-#>     3   parent    68.99  74.02503  -5.035028
-#>     7   parent    52.32  49.74838   2.571618
-#>     7   parent    55.13  49.74838   5.381618
-#>    14   parent    27.27  24.81588   2.454124
-#>    14   parent    26.64  24.81588   1.824124
-#>    21   parent    11.50  12.37885  -0.878849
-#>    21   parent    11.64  12.37885  -0.738849
-#>    35   parent     2.85   3.08022  -0.230219
-#>    35   parent     2.91   3.08022  -0.170219
-#>    50   parent     0.69   0.69396  -0.003958
-#>    50   parent     0.63   0.69396  -0.063958
-#>    75   parent     0.05   0.05789  -0.007888
-#>    75   parent     0.06   0.05789   0.002112
-#>     0       m1     0.00   0.00000   0.000000
-#>     0       m1     0.00   0.00000   0.000000
-#>     1       m1     4.84   4.82149   0.018512
-#>     1       m1     5.64   4.82149   0.818512
-#>     3       m1    12.91  13.06669  -0.156692
-#>     3       m1    12.96  13.06669  -0.106692
-#>     7       m1    22.97  25.10106  -2.131058
-#>     7       m1    24.47  25.10106  -0.631058
-#>    14       m1    41.69  36.72092   4.969077
-#>    14       m1    33.21  36.72092  -3.510923
-#>    21       m1    44.37  41.64835   2.721647
-#>    21       m1    46.44  41.64835   4.791647
-#>    35       m1    41.22  43.26923  -2.049225
-#>    35       m1    37.95  43.26923  -5.319225
-#>    50       m1    41.19  41.17364   0.016361
-#>    50       m1    40.01  41.17364  -1.163639
-#>    75       m1    40.09  36.43122   3.658776
-#>    75       m1    33.85  36.43122  -2.581224
-#>   100       m1    31.04  31.99612  -0.956124
-#>   100       m1    33.13  31.99612   1.133876
-#>   120       m1    25.15  28.82413  -3.674128
-#>   120       m1    33.31  28.82413   4.485872
f.w.value <- mkinfit(SFO_SFO.ff, subset(FOCUS_2006_D, value != 0), err = "value",
+                      m1 = mkinsub("SFO"), use_of_ff = "max")
+f.noweight <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE)
+summary(f.noweight)
+f.irls <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, reweight.method = "obs", quiet = TRUE)
+summary(f.irls)
+f.w.mean <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, weight = "mean", quiet = TRUE)
+summary(f.w.mean)
+f.w.value <- mkinfit(SFO_SFO.ff, subset(FOCUS_2006_D, value != 0), err = "value",
                      quiet = TRUE)
-summary(f.w.value)
#> mkin version:    0.9.47.1 
-#> R version:       3.4.3 
-#> Date of fit:     Tue Jan 30 10:06:04 2018 
-#> Date of summary: Tue Jan 30 10:06:04 2018 
-#> 
-#> Equations:
-#> d_parent/dt = - k_parent * parent
-#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1
-#> 
-#> Model predictions using solution type deSolve 
-#> 
-#> Fitted with method Port using 174 model solutions performed in 0.68 s
-#> 
-#> Weighting: manual
-#> 
-#> Starting values for parameters to be optimised:
-#>                   value   type
-#> parent_0       100.7500  state
-#> k_parent         0.1000 deparm
-#> k_m1             0.1001 deparm
-#> f_parent_to_m1   0.5000 deparm
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>                     value lower upper
-#> parent_0       100.750000  -Inf   Inf
-#> log_k_parent    -2.302585  -Inf   Inf
-#> log_k_m1        -2.301586  -Inf   Inf
-#> f_parent_ilr_1   0.000000  -Inf   Inf
-#> 
-#> Fixed parameter values:
-#>      value  type
-#> m1_0     0 state
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>                Estimate Std. Error    Lower    Upper
-#> parent_0        99.6600   2.712000 94.14000 105.2000
-#> log_k_parent    -2.2980   0.008118 -2.31500  -2.2820
-#> log_k_m1        -5.2410   0.096690 -5.43800  -5.0450
-#> f_parent_ilr_1   0.0231   0.057990 -0.09474   0.1409
-#> 
-#> Parameter correlation:
-#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1
-#> parent_0        1.00000       0.6844 -0.08687        -0.7564
-#> log_k_parent    0.68435       1.0000 -0.12694        -0.5812
-#> log_k_m1       -0.08687      -0.1269  1.00000         0.5195
-#> f_parent_ilr_1 -0.75644      -0.5812  0.51951         1.0000
-#> 
-#> Residual standard error: 0.08396 on 34 degrees of freedom
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>                 Estimate t value    Pr(>t)    Lower     Upper
-#> parent_0       99.660000   36.75 2.957e-29 94.14000 1.052e+02
-#> k_parent        0.100400  123.20 5.927e-47  0.09878 1.021e-01
-#> k_m1            0.005295   10.34 2.447e-12  0.00435 6.444e-03
-#> f_parent_to_m1  0.508200   24.79 1.184e-23  0.46660 5.497e-01
-#> 
-#> Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data   6.461       4 15
-#> parent     6.520       2  7
-#> m1         4.744       2  8
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_m1   0.5082
-#> parent_sink 0.4918
-#> 
-#> Estimated disappearance times:
-#>           DT50   DT90
-#> parent   6.902  22.93
-#> m1     130.916 434.89
-#> 
-#> Data:
-#>  time variable observed predicted   residual    err
-#>     0   parent    99.46  99.65571  -0.195714  99.46
-#>     0   parent   102.04  99.65571   2.384286 102.04
-#>     1   parent    93.50  90.13383   3.366170  93.50
-#>     1   parent    92.50  90.13383   2.366170  92.50
-#>     3   parent    63.23  73.73252 -10.502518  63.23
-#>     3   parent    68.99  73.73252  -4.742518  68.99
-#>     7   parent    52.32  49.34027   2.979728  52.32
-#>     7   parent    55.13  49.34027   5.789728  55.13
-#>    14   parent    27.27  24.42873   2.841271  27.27
-#>    14   parent    26.64  24.42873   2.211271  26.64
-#>    21   parent    11.50  12.09484  -0.594842  11.50
-#>    21   parent    11.64  12.09484  -0.454842  11.64
-#>    35   parent     2.85   2.96482  -0.114824   2.85
-#>    35   parent     2.91   2.96482  -0.054824   2.91
-#>    50   parent     0.69   0.65733   0.032670   0.69
-#>    50   parent     0.63   0.65733  -0.027330   0.63
-#>    75   parent     0.05   0.05339  -0.003386   0.05
-#>    75   parent     0.06   0.05339   0.006614   0.06
-#>     1       m1     4.84   4.82570   0.014301   4.84
-#>     1       m1     5.64   4.82570   0.814301   5.64
-#>     3       m1    12.91  13.06402  -0.154020  12.91
-#>     3       m1    12.96  13.06402  -0.104020  12.96
-#>     7       m1    22.97  25.04656  -2.076564  22.97
-#>     7       m1    24.47  25.04656  -0.576564  24.47
-#>    14       m1    41.69  36.53601   5.153988  41.69
-#>    14       m1    33.21  36.53601  -3.326012  33.21
-#>    21       m1    44.37  41.34639   3.023609  44.37
-#>    21       m1    46.44  41.34639   5.093609  46.44
-#>    35       m1    41.22  42.82669  -1.606690  41.22
-#>    35       m1    37.95  42.82669  -4.876690  37.95
-#>    50       m1    41.19  40.67342   0.516578  41.19
-#>    50       m1    40.01  40.67342  -0.663422  40.01
-#>    75       m1    40.09  35.91105   4.178947  40.09
-#>    75       m1    33.85  35.91105  -2.061053  33.85
-#>   100       m1    31.04  31.48161  -0.441612  31.04
-#>   100       m1    33.13  31.48161   1.648388  33.13
-#>   120       m1    25.15  28.32018  -3.170181  25.15
-#>   120       m1    33.31  28.32018   4.989819  33.31

-
-
+summary(f.w.value)
+# }

+
# NOT RUN {
 # Manual weighting
 dw <- FOCUS_2006_D
 errors <- c(parent = 2, m1 = 1)
 dw$err.man <- errors[FOCUS_2006_D$name]
 f.w.man <- mkinfit(SFO_SFO.ff, dw, err = "err.man", quiet = TRUE)
-summary(f.w.man)
#> mkin version:    0.9.47.1 
-#> R version:       3.4.3 
-#> Date of fit:     Tue Jan 30 10:06:05 2018 
-#> Date of summary: Tue Jan 30 10:06:05 2018 
-#> 
-#> Equations:
-#> d_parent/dt = - k_parent * parent
-#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1
-#> 
-#> Model predictions using solution type deSolve 
-#> 
-#> Fitted with method Port using 297 model solutions performed in 1.178 s
-#> 
-#> Weighting: manual
-#> 
-#> Starting values for parameters to be optimised:
-#>                   value   type
-#> parent_0       100.7500  state
-#> k_parent         0.1000 deparm
-#> k_m1             0.1001 deparm
-#> f_parent_to_m1   0.5000 deparm
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>                     value lower upper
-#> parent_0       100.750000  -Inf   Inf
-#> log_k_parent    -2.302585  -Inf   Inf
-#> log_k_m1        -2.301586  -Inf   Inf
-#> f_parent_ilr_1   0.000000  -Inf   Inf
-#> 
-#> Fixed parameter values:
-#>      value  type
-#> m1_0     0 state
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>                Estimate Std. Error   Lower    Upper
-#> parent_0       99.49000    1.33200 96.7800 102.2000
-#> log_k_parent   -2.32100    0.03550 -2.3930  -2.2490
-#> log_k_m1       -5.24100    0.21280 -5.6730  -4.8100
-#> f_parent_ilr_1  0.04571    0.08966 -0.1361   0.2275
-#> 
-#> Parameter correlation:
-#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1
-#> parent_0        1.00000       0.5312 -0.09456        -0.3351
-#> log_k_parent    0.53123       1.0000 -0.17800        -0.3360
-#> log_k_m1       -0.09456      -0.1780  1.00000         0.7616
-#> f_parent_ilr_1 -0.33514      -0.3360  0.76156         1.0000
-#> 
-#> Residual standard error: 2.628 on 36 degrees of freedom
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>                 Estimate t value    Pr(>t)     Lower     Upper
-#> parent_0       99.490000   74.69 2.221e-41 96.780000 1.022e+02
-#> k_parent        0.098140   28.17 2.012e-26  0.091320 1.055e-01
-#> k_m1            0.005292    4.70 1.873e-05  0.003437 8.148e-03
-#> f_parent_to_m1  0.516200   16.30 1.686e-18  0.452000 5.798e-01
-#> 
-#> Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data   6.400       4 15
-#> parent     6.454       2  7
-#> m1         4.708       2  8
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_m1   0.5162
-#> parent_sink 0.4838
-#> 
-#> Estimated disappearance times:
-#>           DT50   DT90
-#> parent   7.063  23.46
-#> m1     130.971 435.08
-#> 
-#> Data:
-#>  time variable observed predicted   residual err
-#>     0   parent    99.46  99.48598  -0.025976   1
-#>     0   parent   102.04  99.48598   2.554024   1
-#>     1   parent    93.50  90.18612   3.313883   1
-#>     1   parent    92.50  90.18612   2.313883   1
-#>     3   parent    63.23  74.11316 -10.883162   1
-#>     3   parent    68.99  74.11316  -5.123162   1
-#>     7   parent    52.32  50.05029   2.269705   1
-#>     7   parent    55.13  50.05029   5.079705   1
-#>    14   parent    27.27  25.17975   2.090250   1
-#>    14   parent    26.64  25.17975   1.460250   1
-#>    21   parent    11.50  12.66765  -1.167654   1
-#>    21   parent    11.64  12.66765  -1.027654   1
-#>    35   parent     2.85   3.20616  -0.356164   1
-#>    35   parent     2.91   3.20616  -0.296164   1
-#>    50   parent     0.69   0.73562  -0.045619   1
-#>    50   parent     0.63   0.73562  -0.105619   1
-#>    75   parent     0.05   0.06326  -0.013256   1
-#>    75   parent     0.06   0.06326  -0.003256   1
-#>     0       m1     0.00   0.00000   0.000000   2
-#>     0       m1     0.00   0.00000   0.000000   2
-#>     1       m1     4.84   4.78729   0.052713   2
-#>     1       m1     5.64   4.78729   0.852713   2
-#>     3       m1    12.91  12.98785  -0.077848   2
-#>     3       m1    12.96  12.98785  -0.027848   2
-#>     7       m1    22.97  24.99695  -2.026945   2
-#>     7       m1    24.47  24.99695  -0.526945   2
-#>    14       m1    41.69  36.66353   5.026473   2
-#>    14       m1    33.21  36.66353  -3.453527   2
-#>    21       m1    44.37  41.65681   2.713187   2
-#>    21       m1    46.44  41.65681   4.783187   2
-#>    35       m1    41.22  43.35031  -2.130312   2
-#>    35       m1    37.95  43.35031  -5.400312   2
-#>    50       m1    41.19  41.25637  -0.066365   2
-#>    50       m1    40.01  41.25637  -1.246365   2
-#>    75       m1    40.09  36.46057   3.629433   2
-#>    75       m1    33.85  36.46057  -2.610567   2
-#>   100       m1    31.04  31.96929  -0.929288   2
-#>   100       m1    33.13  31.96929   1.160712   2
-#>   120       m1    25.15  28.76062  -3.610616   2
-#>   120       m1    33.31  28.76062   4.549384   2
f.w.man.irls <- mkinfit(SFO_SFO.ff, dw, err = "err.man", quiet = TRUE,
+summary(f.w.man)
+f.w.man.irls <- mkinfit(SFO_SFO.ff, dw, err = "err.man", quiet = TRUE,
                        reweight.method = "obs")
-summary(f.w.man.irls)
#> mkin version:    0.9.47.1 
-#> R version:       3.4.3 
-#> Date of fit:     Tue Jan 30 10:06:08 2018 
-#> Date of summary: Tue Jan 30 10:06:08 2018 
-#> 
-#> Equations:
-#> d_parent/dt = - k_parent * parent
-#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1
-#> 
-#> Model predictions using solution type deSolve 
-#> 
-#> Fitted with method Port using 692 model solutions performed in 2.733 s
-#> 
-#> Weighting: manual
-#> 
-#> Iterative reweighting with method obs 
-#> Final mean squared residuals of observed variables:
-#>    parent        m1 
-#> 11.573407  7.407845 
-#> 
-#> Starting values for parameters to be optimised:
-#>                   value   type
-#> parent_0       100.7500  state
-#> k_parent         0.1000 deparm
-#> k_m1             0.1001 deparm
-#> f_parent_to_m1   0.5000 deparm
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>                     value lower upper
-#> parent_0       100.750000  -Inf   Inf
-#> log_k_parent    -2.302585  -Inf   Inf
-#> log_k_m1        -2.301586  -Inf   Inf
-#> f_parent_ilr_1   0.000000  -Inf   Inf
-#> 
-#> Fixed parameter values:
-#>      value  type
-#> m1_0     0 state
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>                Estimate Std. Error    Lower   Upper
-#> parent_0       99.67000    1.79200 96.04000 103.300
-#> log_k_parent   -2.31200    0.04560 -2.40400  -2.220
-#> log_k_m1       -5.25100    0.12510 -5.50500  -4.998
-#> f_parent_ilr_1  0.03785    0.06318 -0.09027   0.166
-#> 
-#> Parameter correlation:
-#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1
-#> parent_0         1.0000       0.5083  -0.1979        -0.6148
-#> log_k_parent     0.5083       1.0000  -0.3894        -0.6062
-#> log_k_m1        -0.1979      -0.3894   1.0000         0.7417
-#> f_parent_ilr_1  -0.6148      -0.6062   0.7417         1.0000
-#> 
-#> Residual standard error: 1.054 on 36 degrees of freedom
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>                Estimate t value    Pr(>t)     Lower     Upper
-#> parent_0       99.67000  55.630 8.184e-37 96.040000 1.033e+02
-#> k_parent        0.09906  21.930 1.016e-22  0.090310 1.087e-01
-#> k_m1            0.00524   7.996 8.486e-10  0.004066 6.753e-03
-#> f_parent_to_m1  0.51340  23.000 2.038e-23  0.468100 5.584e-01
-#> 
-#> Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data   6.399       4 15
-#> parent     6.466       2  7
-#> m1         4.679       2  8
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_m1   0.5134
-#> parent_sink 0.4866
-#> 
-#> Estimated disappearance times:
-#>           DT50   DT90
-#> parent   6.997  23.24
-#> m1     132.282 439.43
-#> 
-#> Data:
-#>  time variable observed predicted   residual err.ini   err
-#>     0   parent    99.46  99.67218 -2.122e-01       1 3.402
-#>     0   parent   102.04  99.67218  2.368e+00       1 3.402
-#>     1   parent    93.50  90.27153  3.228e+00       1 3.402
-#>     1   parent    92.50  90.27153  2.228e+00       1 3.402
-#>     3   parent    63.23  74.04648 -1.082e+01       1 3.402
-#>     3   parent    68.99  74.04648 -5.056e+00       1 3.402
-#>     7   parent    52.32  49.82092  2.499e+00       1 3.402
-#>     7   parent    55.13  49.82092  5.309e+00       1 3.402
-#>    14   parent    27.27  24.90288  2.367e+00       1 3.402
-#>    14   parent    26.64  24.90288  1.737e+00       1 3.402
-#>    21   parent    11.50  12.44765 -9.476e-01       1 3.402
-#>    21   parent    11.64  12.44765 -8.076e-01       1 3.402
-#>    35   parent     2.85   3.11002 -2.600e-01       1 3.402
-#>    35   parent     2.91   3.11002 -2.000e-01       1 3.402
-#>    50   parent     0.69   0.70375 -1.375e-02       1 3.402
-#>    50   parent     0.63   0.70375 -7.375e-02       1 3.402
-#>    75   parent     0.05   0.05913 -9.134e-03       1 3.402
-#>    75   parent     0.06   0.05913  8.662e-04       1 3.402
-#>     0       m1     0.00   0.00000  0.000e+00       2 2.722
-#>     0       m1     0.00   0.00000  0.000e+00       2 2.722
-#>     1       m1     4.84   4.81328  2.672e-02       2 2.722
-#>     1       m1     5.64   4.81328  8.267e-01       2 2.722
-#>     3       m1    12.91  13.04779 -1.378e-01       2 2.722
-#>     3       m1    12.96  13.04779 -8.779e-02       2 2.722
-#>     7       m1    22.97  25.07615 -2.106e+00       2 2.722
-#>     7       m1    24.47  25.07615 -6.062e-01       2 2.722
-#>    14       m1    41.69  36.70729  4.983e+00       2 2.722
-#>    14       m1    33.21  36.70729 -3.497e+00       2 2.722
-#>    21       m1    44.37  41.65050  2.720e+00       2 2.722
-#>    21       m1    46.44  41.65050  4.790e+00       2 2.722
-#>    35       m1    41.22  43.28866 -2.069e+00       2 2.722
-#>    35       m1    37.95  43.28866 -5.339e+00       2 2.722
-#>    50       m1    41.19  41.19339 -3.386e-03       2 2.722
-#>    50       m1    40.01  41.19339 -1.183e+00       2 2.722
-#>    75       m1    40.09  36.43820  3.652e+00       2 2.722
-#>    75       m1    33.85  36.43820 -2.588e+00       2 2.722
-#>   100       m1    31.04  31.98971 -9.497e-01       2 2.722
-#>   100       m1    33.13  31.98971  1.140e+00       2 2.722
-#>   120       m1    25.15  28.80897 -3.659e+00       2 2.722
-#>   120       m1    33.31  28.80897  4.501e+00       2 2.722

-
+summary(f.w.man.irls) +# }
-

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+

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-- cgit v1.2.1