From 808a679efb69ec6603db6642687d9e8ceb3b3453 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 14 May 2020 18:39:29 +0200 Subject: Add a parms method for mmkin objects --- docs/reference/parms.html | 83 +++++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 80 insertions(+), 3 deletions(-) (limited to 'docs/reference') diff --git a/docs/reference/parms.html b/docs/reference/parms.html index f62b3898..cb705d2c 100644 --- a/docs/reference/parms.html +++ b/docs/reference/parms.html @@ -111,6 +111,9 @@ considering the error structure that was assumed for the fit." />
  • Example evaluation of NAFTA SOP Attachment examples
    • +
  • + Some benchmark timings +
  • @@ -151,6 +154,9 @@ considering the error structure that was assumed for the fit.

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

    Arguments

    @@ -158,7 +164,8 @@ considering the error structure that was assumed for the fit.

    object -

    A fitted model object

    +

    A fitted model object. Methods are implemented for +mkinfit() objects and for mmkin() objects.

    ... @@ -173,7 +180,10 @@ as used internally during the optimisation?

    Value

    -

    A numeric vector of fitted model parameters

    +

    For mkinfit objects, a numeric vector of fitted model parameters. +For mmkin row objects, a matrix with the parameters with a +row for each dataset. If the mmkin object has more than one row, a list of +such matrices is returned.

    Examples

    fit <- mkinfit("SFO", FOCUS_2006_C)
    #> Ordinary least squares optimisation
    #> Sum of squared residuals at call 1: 2388.077
@@ -190,7 +200,74 @@ as used internally during the optimisation?
    
 #> Sum of squared residuals at call 25: 196.5334
 #> Negative log-likelihood at call 31: 26.64668
    #> Optimisation successfully terminated.
    parms(fit)
    #>      parent_0 k_parent_sink         sigma 
 #>    82.4921598     0.3060633     4.6730124 
    parms(fit, transformed = TRUE)
    #>          parent_0 log_k_parent_sink             sigma 
-#>         82.492160         -1.183963          4.673012
    +#> 82.492160 -1.183963 4.673012
    ds <- lapply(experimental_data_for_UBA_2019[6:10], + function(x) subset(x$data[c("name", "time", "value")])) +names(ds) <- paste("Dataset", 6:10) +fits <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE) +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_sink 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 +#> Dataset 7 +#> parent_0 82.666781678 +#> k_parent_sink 0.009647805 +#> sigma 7.040168584 +#> +#> $FOMC +#> Dataset 7 +#> parent_0 92.6837649 +#> alpha 0.4967832 +#> beta 14.1451255 +#> sigma 1.9167519 +#> +#> $DFOP +#> Dataset 7 +#> parent_0 91.058971503 +#> k1 0.044946770 +#> k2 0.002868336 +#> g 0.526942415 +#> sigma 2.221302196 +#>
    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_sink 0.05794659 0.009647805 0.2102974 0.1232258 0.00720421 +#> sigma 5.15274487 7.040168584 3.6769645 6.4669234 6.50457673 +#> +#> $FOMC +#> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10 +#> parent_0 95.558575 92.6837649 90.719787 98.383939 94.8481458 +#> alpha 1.338667 0.4967832 1.639099 1.074460 0.2805272 +#> beta 13.033315 14.1451255 5.007077 4.397126 6.9052224 +#> sigma 1.847671 1.9167519 1.066063 3.146056 1.6222778 +#> +#> $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 +#> sigma 1.35690468 2.221302196 1.34169076 2.87159846 1.942067831 +#>
    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_sink -2.848234 -4.641025 -1.559232 -2.093737 -4.933090 +#> sigma 5.152745 7.040169 3.676964 6.466923 6.504577 +#> +#> $FOMC +#> Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10 +#> parent_0 95.5585751 92.6837649 90.7197870 98.38393897 94.848146 +#> log_alpha 0.2916741 -0.6996015 0.4941466 0.07181816 -1.271085 +#> log_beta 2.5675088 2.6493701 1.6108523 1.48095106 1.932278 +#> 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 +#>