[.mmkin. mkin

+ +

Subsetting method for mmkin objects.

+ + +

# S3 method for mmkin
+[(x, i, j, ..., drop = FALSE)

+ +

Arguments

x: An mmkin object
i: Row index selecting the fits for specific models
j: Column index selecting the fits to specific datasets
...: Not used, only there to satisfy the generic method definition
drop: If FALSE, the method always returns an mmkin object, otherwise either + a list of mkinfit objects or a single mkinfit object.

+ +

Value

+ +

An object of class mmkin.

+ +

Examples

  # Only use one core, to pass R CMD check --as-cran
+  fits <- mmkin(c("SFO", "FOMC"), list(B = FOCUS_2006_B, C = FOCUS_2006_C),
+                cores = 1, quiet = TRUE)
+  fits["FOMC", ]
#>       dataset
+#> model  B       C      
+#>   FOMC List,42 List,42
+#> attr(,"class")
+#> [1] "mmkin"
+#> 
  fits[, "B"]
#>       dataset
+#> model  B      
+#>   SFO  List,42
+#>   FOMC List,42
+#> attr(,"class")
+#> [1] "mmkin"
+#> 
  fits[, "B", drop = TRUE]$FOMC
#> $par
+#>  parent_0 log_alpha  log_beta 
+#> 99.666193  2.549849  5.050586 
+#> 
+#> $ssr
+#> [1] 28.58291
+#> 
+#> $convergence
+#> [1] 0
+#> 
+#> $iterations
+#> [1] 21
+#> 
+#> $evaluations
+#> function gradient 
+#>       25       78 
+#> 
+#> $counts
+#> [1] "both X-convergence and relative convergence (5)"
+#> 
+#> $hessian
+#>             parent_0   log_alpha    log_beta
+#> parent_0    4.123033   -95.69983    93.17699
+#> log_alpha -95.699832  6618.85833 -6352.46648
+#> log_beta   93.176993 -6352.46648  6101.23483
+#> 
+#> $residuals
+#>       parent       parent       parent       parent       parent       parent 
+#>  1.046192647 -3.322396479  3.655156669 -1.705316770  0.406306255 -0.123734689 
+#>       parent       parent 
+#> -0.036886982 -0.006240458 
+#> 
+#> $ms
+#> [1] 3.572863
+#> 
+#> $var_ms
+#>   parent 
+#> 3.572863 
+#> 
+#> $var_ms_unscaled
+#>   parent 
+#> 3.572863 
+#> 
+#> $var_ms_unweighted
+#>   parent 
+#> 3.572863 
+#> 
+#> $rank
+#> [1] 3
+#> 
+#> $df.residual
+#> [1] 5
+#> 
+#> $solution_type
+#> [1] "analytical"
+#> 
+#> $transform_rates
+#> [1] TRUE
+#> 
+#> $transform_fractions
+#> [1] TRUE
+#> 
+#> $method.modFit
+#> [1] "Port"
+#> 
+#> $maxit.modFit
+#> [1] "auto"
+#> 
+#> $calls
+#> [1] 111
+#> 
+#> $time
+#>    user  system elapsed 
+#>   0.256   0.000   0.257 
+#> 
+#> $mkinmod
+#> <mkinmod> model generated with
+#> Use of formation fractions $use_of_ff: min 
+#> Specification $spec:
+#> $parent
+#> $type: FOMC; $sink: TRUE
+#> 
+#> $observed
+#>     name time value
+#> 1 parent    0 98.62
+#> 2 parent    3 81.43
+#> 3 parent    7 53.18
+#> 4 parent   14 34.89
+#> 5 parent   30 10.09
+#> 6 parent   62  1.50
+#> 7 parent   90  0.33
+#> 8 parent  118  0.08
+#> 
+#> $obs_vars
+#> [1] "parent"
+#> 
+#> $predicted
+#>       name       time       value
+#> 1   parent   0.000000 99.66619265
+#> 2   parent   1.191919 90.41690342
+#> 3   parent   2.383838 82.08630014
+#> 4   parent   3.000000 78.10760352
+#> 5   parent   3.575758 74.57722848
+#> 6   parent   4.767677 67.80342415
+#> 7   parent   5.959596 61.68822425
+#> 8   parent   7.000000 56.83515667
+#> 9   parent   7.151515 56.16343898
+#> 10  parent   8.343434 51.16836285
+#> 11  parent   9.535354 46.64890734
+#> 12  parent  10.727273 42.55683931
+#> 13  parent  11.919192 38.84911158
+#> 14  parent  13.111111 35.48727414
+#> 15  parent  14.000000 33.18468323
+#> 16  parent  14.303030 32.43695565
+#> 17  parent  15.494949 29.66740651
+#> 18  parent  16.686869 27.15109578
+#> 19  parent  17.878788 24.86335532
+#> 20  parent  19.070707 22.78206538
+#> 21  parent  20.262626 20.88737647
+#> 22  parent  21.454545 19.16146324
+#> 23  parent  22.646465 17.58830644
+#> 24  parent  23.838384 16.15349953
+#> 25  parent  25.030303 14.84407724
+#> 26  parent  26.222222 13.64836315
+#> 27  parent  27.414141 12.55583436
+#> 28  parent  28.606061 11.55700107
+#> 29  parent  29.797980 10.64329940
+#> 30  parent  30.000000 10.49630626
+#> 31  parent  30.989899  9.80699593
+#> 32  parent  32.181818  9.04110261
+#> 33  parent  33.373737  8.33930082
+#> 34  parent  34.565657  7.69587362
+#> 35  parent  35.757576  7.10564515
+#> 36  parent  36.949495  6.56392657
+#> 37  parent  38.141414  6.06646759
+#> 38  parent  39.333333  5.60941311
+#> 39  parent  40.525253  5.18926438
+#> 40  parent  41.717172  4.80284421
+#> 41  parent  42.909091  4.44726569
+#> 42  parent  44.101010  4.11990420
+#> 43  parent  45.292929  3.81837216
+#> 44  parent  46.484848  3.54049644
+#> 45  parent  47.676768  3.28429799
+#> 46  parent  48.868687  3.04797350
+#> 47  parent  50.060606  2.82987892
+#> 48  parent  51.252525  2.62851456
+#> 49  parent  52.444444  2.44251172
+#> 50  parent  53.636364  2.27062056
+#> 51  parent  54.828283  2.11169922
+#> 52  parent  56.020202  1.96470393
+#> 53  parent  57.212121  1.82868009
+#> 54  parent  58.404040  1.70275424
+#> 55  parent  59.595960  1.58612677
+#> 56  parent  60.787879  1.47806529
+#> 57  parent  61.979798  1.37789865
+#> 58  parent  62.000000  1.37626531
+#> 59  parent  63.171717  1.28501157
+#> 60  parent  64.363636  1.19883967
+#> 61  parent  65.555556  1.11886504
+#> 62  parent  66.747475  1.04461220
+#> 63  parent  67.939394  0.97564441
+#> 64  parent  69.131313  0.91156031
+#> 65  parent  70.323232  0.85199096
+#> 66  parent  71.515152  0.79659697
+#> 67  parent  72.707071  0.74506609
+#> 68  parent  73.898990  0.69711084
+#> 69  parent  75.090909  0.65246649
+#> 70  parent  76.282828  0.61088912
+#> 71  parent  77.474747  0.57215389
+#> 72  parent  78.666667  0.53605348
+#> 73  parent  79.858586  0.50239663
+#> 74  parent  81.050505  0.47100683
+#> 75  parent  82.242424  0.44172111
+#> 76  parent  83.434343  0.41438896
+#> 77  parent  84.626263  0.38887128
+#> 78  parent  85.818182  0.36503953
+#> 79  parent  87.010101  0.34277481
+#> 80  parent  88.202020  0.32196716
+#> 81  parent  89.393939  0.30251479
+#> 82  parent  90.000000  0.29311302
+#> 83  parent  90.585859  0.28432347
+#> 84  parent  91.777778  0.26730596
+#> 85  parent  92.969697  0.25138141
+#> 86  parent  94.161616  0.23647487
+#> 87  parent  95.353535  0.22251689
+#> 88  parent  96.545455  0.20944302
+#> 89  parent  97.737374  0.19719349
+#> 90  parent  98.929293  0.18571281
+#> 91  parent 100.121212  0.17494947
+#> 92  parent 101.313131  0.16485560
+#> 93  parent 102.505051  0.15538676
+#> 94  parent 103.696970  0.14650163
+#> 95  parent 104.888889  0.13816179
+#> 96  parent 106.080808  0.13033150
+#> 97  parent 107.272727  0.12297753
+#> 98  parent 108.464646  0.11606895
+#> 99  parent 109.656566  0.10957695
+#> 100 parent 110.848485  0.10347470
+#> 101 parent 112.040404  0.09773723
+#> 102 parent 113.232323  0.09234125
+#> 103 parent 114.424242  0.08726506
+#> 104 parent 115.616162  0.08248842
+#> 105 parent 116.808081  0.07799245
+#> 106 parent 118.000000  0.07375954
+#> 
+#> $cost
+#> function (P) 
+#> {
+#>     assign("calls", calls + 1, inherits = TRUE)
+#>     if (trace_parms) 
+#>         cat(P, "\n")
+#>     if (length(state.ini.optim) > 0) {
+#>         odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed)
+#>         names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames)
+#>     }
+#>     else {
+#>         odeini <- state.ini.fixed
+#>         names(odeini) <- state.ini.fixed.boxnames
+#>     }
+#>     odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], 
+#>         transparms.fixed)
+#>     parms <- backtransform_odeparms(odeparms, mkinmod, transform_rates = transform_rates, 
+#>         transform_fractions = transform_fractions)
+#>     out <- mkinpredict(mkinmod, parms, odeini, outtimes, solution_type = solution_type, 
+#>         use_compiled = use_compiled, method.ode = method.ode, 
+#>         atol = atol, rtol = rtol, ...)
+#>     assign("out_predicted", out, inherits = TRUE)
+#>     mC <- modCost(out, observed, y = "value", err = err, weight = weight, 
+#>         scaleVar = scaleVar)
+#>     if (mC$model < cost.old) {
+#>         if (!quiet) 
+#>             cat("Model cost at call ", calls, ": ", mC$model, 
+#>                 "\n")
+#>         if (plot) {
+#>             outtimes_plot = seq(min(observed$time), max(observed$time), 
+#>                 length.out = 100)
+#>             out_plot <- mkinpredict(mkinmod, parms, odeini, outtimes_plot, 
+#>                 solution_type = solution_type, use_compiled = use_compiled, 
+#>                 method.ode = method.ode, atol = atol, rtol = rtol, 
+#>                 ...)
+#>             plot(0, type = "n", xlim = range(observed$time), 
+#>                 ylim = c(0, max(observed$value, na.rm = TRUE)), 
+#>                 xlab = "Time", ylab = "Observed")
+#>             col_obs <- pch_obs <- 1:length(obs_vars)
+#>             lty_obs <- rep(1, length(obs_vars))
+#>             names(col_obs) <- names(pch_obs) <- names(lty_obs) <- obs_vars
+#>             for (obs_var in obs_vars) {
+#>                 points(subset(observed, name == obs_var, c(time, 
+#>                   value)), pch = pch_obs[obs_var], col = col_obs[obs_var])
+#>             }
+#>             matlines(out_plot$time, out_plot[-1], col = col_obs, 
+#>                 lty = lty_obs)
+#>             legend("topright", inset = c(0.05, 0.05), legend = obs_vars, 
+#>                 col = col_obs, pch = pch_obs, lty = 1:length(pch_obs))
+#>         }
+#>         assign("cost.old", mC$model, inherits = TRUE)
+#>     }
+#>     return(mC)
+#> }
+#> <environment: 0x27fc328>
+#> 
+#> $cost_notrans
+#> function (P) 
+#> {
+#>     if (length(state.ini.optim) > 0) {
+#>         odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed)
+#>         names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames)
+#>     }
+#>     else {
+#>         odeini <- state.ini.fixed
+#>         names(odeini) <- state.ini.fixed.boxnames
+#>     }
+#>     odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], 
+#>         parms.fixed)
+#>     out <- mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = solution_type, 
+#>         use_compiled = use_compiled, method.ode = method.ode, 
+#>         atol = atol, rtol = rtol, ...)
+#>     mC <- modCost(out, observed, y = "value", err = err, weight = weight, 
+#>         scaleVar = scaleVar)
+#>     return(mC)
+#> }
+#> <environment: 0x27fc328>
+#> 
+#> $hessian_notrans
+#>            parent_0     alpha       beta
+#> parent_0  4.1230329 -7.473531  0.5968527
+#> alpha    -7.4735307 40.365690 -3.1777189
+#> beta      0.5968527 -3.177719  0.2503425
+#> 
+#> $start
+#>          value   type
+#> parent_0 98.62  state
+#> alpha     1.00 deparm
+#> beta     10.00 deparm
+#> 
+#> $start_transformed
+#>               value lower upper
+#> parent_0  98.620000  -Inf   Inf
+#> log_alpha  0.000000  -Inf   Inf
+#> log_beta   2.302585  -Inf   Inf
+#> 
+#> $fixed
+#> [1] value type 
+#> <0 rows> (or 0-length row.names)
+#> 
+#> $data
+#>   time variable observed   predicted     residual
+#> 1    0   parent    98.62 99.66619265 -1.046192647
+#> 2    3   parent    81.43 78.10760352  3.322396479
+#> 3    7   parent    53.18 56.83515667 -3.655156669
+#> 4   14   parent    34.89 33.18468323  1.705316770
+#> 5   30   parent    10.09 10.49630626 -0.406306255
+#> 6   62   parent     1.50  1.37626531  0.123734689
+#> 7   90   parent     0.33  0.29311302  0.036886982
+#> 8  118   parent     0.08  0.07375954  0.006240458
+#> 
+#> $atol
+#> [1] 1e-08
+#> 
+#> $rtol
+#> [1] 1e-10
+#> 
+#> $weight.ini
+#> [1] "none"
+#> 
+#> $reweight.tol
+#> [1] 1e-08
+#> 
+#> $reweight.max.iter
+#> [1] 10
+#> 
+#> $bparms.optim
+#>  parent_0     alpha      beta 
+#>  99.66619  12.80517 156.11390 
+#> 
+#> $bparms.fixed
+#> numeric(0)
+#> 
+#> $bparms.ode
+#>     alpha      beta 
+#>  12.80517 156.11390 
+#> 
+#> $bparms.state
+#>   parent 
+#> 99.66619 
+#> 
+#> $date
+#> [1] "Thu Oct  6 09:17:52 2016"
+#> 
+#> attr(,"class")
+#> [1] "mkinfit" "modFit" 
+#> 
  fits["SFO", "B"]
#>      dataset
+#> model B      
+#>   SFO List,42
+#> attr(,"class")
+#> [1] "mmkin"
+#> 
  fits[["SFO", "B"]] # This is equivalent to
#> $par
+#>          parent_0 log_k_parent_sink 
+#>         99.174072         -2.549028 
+#> 
+#> $ssr
+#> [1] 30.65564
+#> 
+#> $convergence
+#> [1] 0
+#> 
+#> $iterations
+#> [1] 5
+#> 
+#> $evaluations
+#> function gradient 
+#>        8       15 
+#> 
+#> $counts
+#> [1] "relative convergence (4)"
+#> 
+#> $hessian
+#>                     parent_0 log_k_parent_sink
+#> parent_0            4.163631         -94.09343
+#> log_k_parent_sink -94.093431        6311.34610
+#> 
+#> $residuals
+#>      parent      parent      parent      parent      parent      parent 
+#>  0.55407218 -2.98452128  4.20445742 -1.68599939 -0.58185357 -0.72033730 
+#>      parent      parent 
+#> -0.24260405 -0.07020339 
+#> 
+#> $ms
+#> [1] 3.831956
+#> 
+#> $var_ms
+#>   parent 
+#> 3.831956 
+#> 
+#> $var_ms_unscaled
+#>   parent 
+#> 3.831956 
+#> 
+#> $var_ms_unweighted
+#>   parent 
+#> 3.831956 
+#> 
+#> $rank
+#> [1] 2
+#> 
+#> $df.residual
+#> [1] 6
+#> 
+#> $solution_type
+#> [1] "analytical"
+#> 
+#> $transform_rates
+#> [1] TRUE
+#> 
+#> $transform_fractions
+#> [1] TRUE
+#> 
+#> $method.modFit
+#> [1] "Port"
+#> 
+#> $maxit.modFit
+#> [1] "auto"
+#> 
+#> $calls
+#> [1] 29
+#> 
+#> $time
+#>    user  system elapsed 
+#>   0.068   0.000   0.068 
+#> 
+#> $mkinmod
+#> <mkinmod> model generated with
+#> Use of formation fractions $use_of_ff: min 
+#> Specification $spec:
+#> $parent
+#> $type: SFO; $sink: TRUE
+#> Coefficient matrix $coefmat available
+#> 
+#> $observed
+#>     name time value
+#> 1 parent    0 98.62
+#> 2 parent    3 81.43
+#> 3 parent    7 53.18
+#> 4 parent   14 34.89
+#> 5 parent   30 10.09
+#> 6 parent   62  1.50
+#> 7 parent   90  0.33
+#> 8 parent  118  0.08
+#> 
+#> $obs_vars
+#> [1] "parent"
+#> 
+#> $predicted
+#>       name       time       value
+#> 1   parent   0.000000 99.17407218
+#> 2   parent   1.191919 90.35253561
+#> 3   parent   2.383838 82.31567498
+#> 4   parent   3.000000 78.44547872
+#> 5   parent   3.575758 74.99369333
+#> 6   parent   4.767677 68.32300215
+#> 7   parent   5.959596 62.24566915
+#> 8   parent   7.000000 57.38445742
+#> 9   parent   7.151515 56.70891509
+#> 10  parent   8.343434 51.66465547
+#> 11  parent   9.535354 47.06908288
+#> 12  parent  10.727273 42.88228661
+#> 13  parent  11.919192 39.06790599
+#> 14  parent  13.111111 35.59281463
+#> 15  parent  14.000000 33.20400061
+#> 16  parent  14.303030 32.42683275
+#> 17  parent  15.494949 29.54246504
+#> 18  parent  16.686869 26.91466193
+#> 19  parent  17.878788 24.52060198
+#> 20  parent  19.070707 22.33949373
+#> 21  parent  20.262626 20.35239512
+#> 22  parent  21.454545 18.54204899
+#> 23  parent  22.646465 16.89273320
+#> 24  parent  23.838384 15.39012410
+#> 25  parent  25.030303 14.02117212
+#> 26  parent  26.222222 12.77398846
+#> 27  parent  27.414141 11.63774182
+#> 28  parent  28.606061 10.60256435
+#> 29  parent  29.797980  9.65946594
+#> 30  parent  30.000000  9.50814643
+#> 31  parent  30.989899  8.80025617
+#> 32  parent  32.181818  8.01747313
+#> 33  parent  33.373737  7.30431867
+#> 34  parent  34.565657  6.65459931
+#> 35  parent  35.757576  6.06267251
+#> 36  parent  36.949495  5.52339762
+#> 37  parent  38.141414  5.03209124
+#> 38  parent  39.333333  4.58448658
+#> 39  parent  40.525253  4.17669637
+#> 40  parent  41.717172  3.80517911
+#> 41  parent  42.909091  3.46670832
+#> 42  parent  44.101010  3.15834451
+#> 43  parent  45.292929  2.87740968
+#> 44  parent  46.484848  2.62146400
+#> 45  parent  47.676768  2.38828471
+#> 46  parent  48.868687  2.17584671
+#> 47  parent  50.060606  1.98230508
+#> 48  parent  51.252525  1.80597899
+#> 49  parent  52.444444  1.64533711
+#> 50  parent  53.636364  1.49898432
+#> 51  parent  54.828283  1.36564963
+#> 52  parent  56.020202  1.24417505
+#> 53  parent  57.212121  1.13350565
+#> 54  parent  58.404040  1.03268029
+#> 55  parent  59.595960  0.94082335
+#> 56  parent  60.787879  0.85713708
+#> 57  parent  61.979798  0.78089471
+#> 58  parent  62.000000  0.77966270
+#> 59  parent  63.171717  0.71143411
+#> 60  parent  64.363636  0.64815202
+#> 61  parent  65.555556  0.59049888
+#> 62  parent  66.747475  0.53797399
+#> 63  parent  67.939394  0.49012119
+#> 64  parent  69.131313  0.44652489
+#> 65  parent  70.323232  0.40680649
+#> 66  parent  71.515152  0.37062104
+#> 67  parent  72.707071  0.33765429
+#> 68  parent  73.898990  0.30761993
+#> 69  parent  75.090909  0.28025713
+#> 70  parent  76.282828  0.25532825
+#> 71  parent  77.474747  0.23261679
+#> 72  parent  78.666667  0.21192552
+#> 73  parent  79.858586  0.19307474
+#> 74  parent  81.050505  0.17590074
+#> 75  parent  82.242424  0.16025436
+#> 76  parent  83.434343  0.14599973
+#> 77  parent  84.626263  0.13301305
+#> 78  parent  85.818182  0.12118154
+#> 79  parent  87.010101  0.11040244
+#> 80  parent  88.202020  0.10058214
+#> 81  parent  89.393939  0.09163535
+#> 82  parent  90.000000  0.08739595
+#> 83  parent  90.585859  0.08348439
+#> 84  parent  91.777778  0.07605845
+#> 85  parent  92.969697  0.06929305
+#> 86  parent  94.161616  0.06312943
+#> 87  parent  95.353535  0.05751406
+#> 88  parent  96.545455  0.05239819
+#> 89  parent  97.737374  0.04773737
+#> 90  parent  98.929293  0.04349113
+#> 91  parent 100.121212  0.03962259
+#> 92  parent 101.313131  0.03609816
+#> 93  parent 102.505051  0.03288723
+#> 94  parent 103.696970  0.02996191
+#> 95  parent 104.888889  0.02729679
+#> 96  parent 106.080808  0.02486874
+#> 97  parent 107.272727  0.02265667
+#> 98  parent 108.464646  0.02064136
+#> 99  parent 109.656566  0.01880531
+#> 100 parent 110.848485  0.01713257
+#> 101 parent 112.040404  0.01560863
+#> 102 parent 113.232323  0.01422024
+#> 103 parent 114.424242  0.01295535
+#> 104 parent 115.616162  0.01180297
+#> 105 parent 116.808081  0.01075310
+#> 106 parent 118.000000  0.00979661
+#> 
+#> $cost
+#> function (P) 
+#> {
+#>     assign("calls", calls + 1, inherits = TRUE)
+#>     if (trace_parms) 
+#>         cat(P, "\n")
+#>     if (length(state.ini.optim) > 0) {
+#>         odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed)
+#>         names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames)
+#>     }
+#>     else {
+#>         odeini <- state.ini.fixed
+#>         names(odeini) <- state.ini.fixed.boxnames
+#>     }
+#>     odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], 
+#>         transparms.fixed)
+#>     parms <- backtransform_odeparms(odeparms, mkinmod, transform_rates = transform_rates, 
+#>         transform_fractions = transform_fractions)
+#>     out <- mkinpredict(mkinmod, parms, odeini, outtimes, solution_type = solution_type, 
+#>         use_compiled = use_compiled, method.ode = method.ode, 
+#>         atol = atol, rtol = rtol, ...)
+#>     assign("out_predicted", out, inherits = TRUE)
+#>     mC <- modCost(out, observed, y = "value", err = err, weight = weight, 
+#>         scaleVar = scaleVar)
+#>     if (mC$model < cost.old) {
+#>         if (!quiet) 
+#>             cat("Model cost at call ", calls, ": ", mC$model, 
+#>                 "\n")
+#>         if (plot) {
+#>             outtimes_plot = seq(min(observed$time), max(observed$time), 
+#>                 length.out = 100)
+#>             out_plot <- mkinpredict(mkinmod, parms, odeini, outtimes_plot, 
+#>                 solution_type = solution_type, use_compiled = use_compiled, 
+#>                 method.ode = method.ode, atol = atol, rtol = rtol, 
+#>                 ...)
+#>             plot(0, type = "n", xlim = range(observed$time), 
+#>                 ylim = c(0, max(observed$value, na.rm = TRUE)), 
+#>                 xlab = "Time", ylab = "Observed")
+#>             col_obs <- pch_obs <- 1:length(obs_vars)
+#>             lty_obs <- rep(1, length(obs_vars))
+#>             names(col_obs) <- names(pch_obs) <- names(lty_obs) <- obs_vars
+#>             for (obs_var in obs_vars) {
+#>                 points(subset(observed, name == obs_var, c(time, 
+#>                   value)), pch = pch_obs[obs_var], col = col_obs[obs_var])
+#>             }
+#>             matlines(out_plot$time, out_plot[-1], col = col_obs, 
+#>                 lty = lty_obs)
+#>             legend("topright", inset = c(0.05, 0.05), legend = obs_vars, 
+#>                 col = col_obs, pch = pch_obs, lty = 1:length(pch_obs))
+#>         }
+#>         assign("cost.old", mC$model, inherits = TRUE)
+#>     }
+#>     return(mC)
+#> }
+#> <environment: 0x2e966b0>
+#> 
+#> $cost_notrans
+#> function (P) 
+#> {
+#>     if (length(state.ini.optim) > 0) {
+#>         odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed)
+#>         names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames)
+#>     }
+#>     else {
+#>         odeini <- state.ini.fixed
+#>         names(odeini) <- state.ini.fixed.boxnames
+#>     }
+#>     odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], 
+#>         parms.fixed)
+#>     out <- mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = solution_type, 
+#>         use_compiled = use_compiled, method.ode = method.ode, 
+#>         atol = atol, rtol = rtol, ...)
+#>     mC <- modCost(out, observed, y = "value", err = err, weight = weight, 
+#>         scaleVar = scaleVar)
+#>     return(mC)
+#> }
+#> <environment: 0x2e966b0>
+#> 
+#> $hessian_notrans
+#>                   parent_0 k_parent_sink
+#> parent_0          4.163631     -1203.894
+#> k_parent_sink -1203.893702   1033188.753
+#> 
+#> $start
+#>               value   type
+#> parent_0      98.62  state
+#> k_parent_sink  0.10 deparm
+#> 
+#> $start_transformed
+#>                       value lower upper
+#> parent_0          98.620000  -Inf   Inf
+#> log_k_parent_sink -2.302585  -Inf   Inf
+#> 
+#> $fixed
+#> [1] value type 
+#> <0 rows> (or 0-length row.names)
+#> 
+#> $data
+#>   time variable observed   predicted    residual
+#> 1    0   parent    98.62 99.17407218 -0.55407218
+#> 2    3   parent    81.43 78.44547872  2.98452128
+#> 3    7   parent    53.18 57.38445742 -4.20445742
+#> 4   14   parent    34.89 33.20400061  1.68599939
+#> 5   30   parent    10.09  9.50814643  0.58185357
+#> 6   62   parent     1.50  0.77966270  0.72033730
+#> 7   90   parent     0.33  0.08739595  0.24260405
+#> 8  118   parent     0.08  0.00979661  0.07020339
+#> 
+#> $atol
+#> [1] 1e-08
+#> 
+#> $rtol
+#> [1] 1e-10
+#> 
+#> $weight.ini
+#> [1] "none"
+#> 
+#> $reweight.tol
+#> [1] 1e-08
+#> 
+#> $reweight.max.iter
+#> [1] 10
+#> 
+#> $bparms.optim
+#>      parent_0 k_parent_sink 
+#>   99.17407218    0.07815759 
+#> 
+#> $bparms.fixed
+#> numeric(0)
+#> 
+#> $bparms.ode
+#> k_parent_sink 
+#>    0.07815759 
+#> 
+#> $bparms.state
+#>   parent 
+#> 99.17407 
+#> 
+#> $date
+#> [1] "Thu Oct  6 09:17:51 2016"
+#> 
+#> attr(,"class")
+#> [1] "mkinfit" "modFit" 
+#> 
  fits["SFO", "B", drop = TRUE]
#> [[1]]
+#> $par
+#>          parent_0 log_k_parent_sink 
+#>         99.174072         -2.549028 
+#> 
+#> $ssr
+#> [1] 30.65564
+#> 
+#> $convergence
+#> [1] 0
+#> 
+#> $iterations
+#> [1] 5
+#> 
+#> $evaluations
+#> function gradient 
+#>        8       15 
+#> 
+#> $counts
+#> [1] "relative convergence (4)"
+#> 
+#> $hessian
+#>                     parent_0 log_k_parent_sink
+#> parent_0            4.163631         -94.09343
+#> log_k_parent_sink -94.093431        6311.34610
+#> 
+#> $residuals
+#>      parent      parent      parent      parent      parent      parent 
+#>  0.55407218 -2.98452128  4.20445742 -1.68599939 -0.58185357 -0.72033730 
+#>      parent      parent 
+#> -0.24260405 -0.07020339 
+#> 
+#> $ms
+#> [1] 3.831956
+#> 
+#> $var_ms
+#>   parent 
+#> 3.831956 
+#> 
+#> $var_ms_unscaled
+#>   parent 
+#> 3.831956 
+#> 
+#> $var_ms_unweighted
+#>   parent 
+#> 3.831956 
+#> 
+#> $rank
+#> [1] 2
+#> 
+#> $df.residual
+#> [1] 6
+#> 
+#> $solution_type
+#> [1] "analytical"
+#> 
+#> $transform_rates
+#> [1] TRUE
+#> 
+#> $transform_fractions
+#> [1] TRUE
+#> 
+#> $method.modFit
+#> [1] "Port"
+#> 
+#> $maxit.modFit
+#> [1] "auto"
+#> 
+#> $calls
+#> [1] 29
+#> 
+#> $time
+#>    user  system elapsed 
+#>   0.068   0.000   0.068 
+#> 
+#> $mkinmod
+#> <mkinmod> model generated with
+#> Use of formation fractions $use_of_ff: min 
+#> Specification $spec:
+#> $parent
+#> $type: SFO; $sink: TRUE
+#> Coefficient matrix $coefmat available
+#> 
+#> $observed
+#>     name time value
+#> 1 parent    0 98.62
+#> 2 parent    3 81.43
+#> 3 parent    7 53.18
+#> 4 parent   14 34.89
+#> 5 parent   30 10.09
+#> 6 parent   62  1.50
+#> 7 parent   90  0.33
+#> 8 parent  118  0.08
+#> 
+#> $obs_vars
+#> [1] "parent"
+#> 
+#> $predicted
+#>       name       time       value
+#> 1   parent   0.000000 99.17407218
+#> 2   parent   1.191919 90.35253561
+#> 3   parent   2.383838 82.31567498
+#> 4   parent   3.000000 78.44547872
+#> 5   parent   3.575758 74.99369333
+#> 6   parent   4.767677 68.32300215
+#> 7   parent   5.959596 62.24566915
+#> 8   parent   7.000000 57.38445742
+#> 9   parent   7.151515 56.70891509
+#> 10  parent   8.343434 51.66465547
+#> 11  parent   9.535354 47.06908288
+#> 12  parent  10.727273 42.88228661
+#> 13  parent  11.919192 39.06790599
+#> 14  parent  13.111111 35.59281463
+#> 15  parent  14.000000 33.20400061
+#> 16  parent  14.303030 32.42683275
+#> 17  parent  15.494949 29.54246504
+#> 18  parent  16.686869 26.91466193
+#> 19  parent  17.878788 24.52060198
+#> 20  parent  19.070707 22.33949373
+#> 21  parent  20.262626 20.35239512
+#> 22  parent  21.454545 18.54204899
+#> 23  parent  22.646465 16.89273320
+#> 24  parent  23.838384 15.39012410
+#> 25  parent  25.030303 14.02117212
+#> 26  parent  26.222222 12.77398846
+#> 27  parent  27.414141 11.63774182
+#> 28  parent  28.606061 10.60256435
+#> 29  parent  29.797980  9.65946594
+#> 30  parent  30.000000  9.50814643
+#> 31  parent  30.989899  8.80025617
+#> 32  parent  32.181818  8.01747313
+#> 33  parent  33.373737  7.30431867
+#> 34  parent  34.565657  6.65459931
+#> 35  parent  35.757576  6.06267251
+#> 36  parent  36.949495  5.52339762
+#> 37  parent  38.141414  5.03209124
+#> 38  parent  39.333333  4.58448658
+#> 39  parent  40.525253  4.17669637
+#> 40  parent  41.717172  3.80517911
+#> 41  parent  42.909091  3.46670832
+#> 42  parent  44.101010  3.15834451
+#> 43  parent  45.292929  2.87740968
+#> 44  parent  46.484848  2.62146400
+#> 45  parent  47.676768  2.38828471
+#> 46  parent  48.868687  2.17584671
+#> 47  parent  50.060606  1.98230508
+#> 48  parent  51.252525  1.80597899
+#> 49  parent  52.444444  1.64533711
+#> 50  parent  53.636364  1.49898432
+#> 51  parent  54.828283  1.36564963
+#> 52  parent  56.020202  1.24417505
+#> 53  parent  57.212121  1.13350565
+#> 54  parent  58.404040  1.03268029
+#> 55  parent  59.595960  0.94082335
+#> 56  parent  60.787879  0.85713708
+#> 57  parent  61.979798  0.78089471
+#> 58  parent  62.000000  0.77966270
+#> 59  parent  63.171717  0.71143411
+#> 60  parent  64.363636  0.64815202
+#> 61  parent  65.555556  0.59049888
+#> 62  parent  66.747475  0.53797399
+#> 63  parent  67.939394  0.49012119
+#> 64  parent  69.131313  0.44652489
+#> 65  parent  70.323232  0.40680649
+#> 66  parent  71.515152  0.37062104
+#> 67  parent  72.707071  0.33765429
+#> 68  parent  73.898990  0.30761993
+#> 69  parent  75.090909  0.28025713
+#> 70  parent  76.282828  0.25532825
+#> 71  parent  77.474747  0.23261679
+#> 72  parent  78.666667  0.21192552
+#> 73  parent  79.858586  0.19307474
+#> 74  parent  81.050505  0.17590074
+#> 75  parent  82.242424  0.16025436
+#> 76  parent  83.434343  0.14599973
+#> 77  parent  84.626263  0.13301305
+#> 78  parent  85.818182  0.12118154
+#> 79  parent  87.010101  0.11040244
+#> 80  parent  88.202020  0.10058214
+#> 81  parent  89.393939  0.09163535
+#> 82  parent  90.000000  0.08739595
+#> 83  parent  90.585859  0.08348439
+#> 84  parent  91.777778  0.07605845
+#> 85  parent  92.969697  0.06929305
+#> 86  parent  94.161616  0.06312943
+#> 87  parent  95.353535  0.05751406
+#> 88  parent  96.545455  0.05239819
+#> 89  parent  97.737374  0.04773737
+#> 90  parent  98.929293  0.04349113
+#> 91  parent 100.121212  0.03962259
+#> 92  parent 101.313131  0.03609816
+#> 93  parent 102.505051  0.03288723
+#> 94  parent 103.696970  0.02996191
+#> 95  parent 104.888889  0.02729679
+#> 96  parent 106.080808  0.02486874
+#> 97  parent 107.272727  0.02265667
+#> 98  parent 108.464646  0.02064136
+#> 99  parent 109.656566  0.01880531
+#> 100 parent 110.848485  0.01713257
+#> 101 parent 112.040404  0.01560863
+#> 102 parent 113.232323  0.01422024
+#> 103 parent 114.424242  0.01295535
+#> 104 parent 115.616162  0.01180297
+#> 105 parent 116.808081  0.01075310
+#> 106 parent 118.000000  0.00979661
+#> 
+#> $cost
+#> function (P) 
+#> {
+#>     assign("calls", calls + 1, inherits = TRUE)
+#>     if (trace_parms) 
+#>         cat(P, "\n")
+#>     if (length(state.ini.optim) > 0) {
+#>         odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed)
+#>         names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames)
+#>     }
+#>     else {
+#>         odeini <- state.ini.fixed
+#>         names(odeini) <- state.ini.fixed.boxnames
+#>     }
+#>     odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], 
+#>         transparms.fixed)
+#>     parms <- backtransform_odeparms(odeparms, mkinmod, transform_rates = transform_rates, 
+#>         transform_fractions = transform_fractions)
+#>     out <- mkinpredict(mkinmod, parms, odeini, outtimes, solution_type = solution_type, 
+#>         use_compiled = use_compiled, method.ode = method.ode, 
+#>         atol = atol, rtol = rtol, ...)
+#>     assign("out_predicted", out, inherits = TRUE)
+#>     mC <- modCost(out, observed, y = "value", err = err, weight = weight, 
+#>         scaleVar = scaleVar)
+#>     if (mC$model < cost.old) {
+#>         if (!quiet) 
+#>             cat("Model cost at call ", calls, ": ", mC$model, 
+#>                 "\n")
+#>         if (plot) {
+#>             outtimes_plot = seq(min(observed$time), max(observed$time), 
+#>                 length.out = 100)
+#>             out_plot <- mkinpredict(mkinmod, parms, odeini, outtimes_plot, 
+#>                 solution_type = solution_type, use_compiled = use_compiled, 
+#>                 method.ode = method.ode, atol = atol, rtol = rtol, 
+#>                 ...)
+#>             plot(0, type = "n", xlim = range(observed$time), 
+#>                 ylim = c(0, max(observed$value, na.rm = TRUE)), 
+#>                 xlab = "Time", ylab = "Observed")
+#>             col_obs <- pch_obs <- 1:length(obs_vars)
+#>             lty_obs <- rep(1, length(obs_vars))
+#>             names(col_obs) <- names(pch_obs) <- names(lty_obs) <- obs_vars
+#>             for (obs_var in obs_vars) {
+#>                 points(subset(observed, name == obs_var, c(time, 
+#>                   value)), pch = pch_obs[obs_var], col = col_obs[obs_var])
+#>             }
+#>             matlines(out_plot$time, out_plot[-1], col = col_obs, 
+#>                 lty = lty_obs)
+#>             legend("topright", inset = c(0.05, 0.05), legend = obs_vars, 
+#>                 col = col_obs, pch = pch_obs, lty = 1:length(pch_obs))
+#>         }
+#>         assign("cost.old", mC$model, inherits = TRUE)
+#>     }
+#>     return(mC)
+#> }
+#> <environment: 0x2e966b0>
+#> 
+#> $cost_notrans
+#> function (P) 
+#> {
+#>     if (length(state.ini.optim) > 0) {
+#>         odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed)
+#>         names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames)
+#>     }
+#>     else {
+#>         odeini <- state.ini.fixed
+#>         names(odeini) <- state.ini.fixed.boxnames
+#>     }
+#>     odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], 
+#>         parms.fixed)
+#>     out <- mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = solution_type, 
+#>         use_compiled = use_compiled, method.ode = method.ode, 
+#>         atol = atol, rtol = rtol, ...)
+#>     mC <- modCost(out, observed, y = "value", err = err, weight = weight, 
+#>         scaleVar = scaleVar)
+#>     return(mC)
+#> }
+#> <environment: 0x2e966b0>
+#> 
+#> $hessian_notrans
+#>                   parent_0 k_parent_sink
+#> parent_0          4.163631     -1203.894
+#> k_parent_sink -1203.893702   1033188.753
+#> 
+#> $start
+#>               value   type
+#> parent_0      98.62  state
+#> k_parent_sink  0.10 deparm
+#> 
+#> $start_transformed
+#>                       value lower upper
+#> parent_0          98.620000  -Inf   Inf
+#> log_k_parent_sink -2.302585  -Inf   Inf
+#> 
+#> $fixed
+#> [1] value type 
+#> <0 rows> (or 0-length row.names)
+#> 
+#> $data
+#>   time variable observed   predicted    residual
+#> 1    0   parent    98.62 99.17407218 -0.55407218
+#> 2    3   parent    81.43 78.44547872  2.98452128
+#> 3    7   parent    53.18 57.38445742 -4.20445742
+#> 4   14   parent    34.89 33.20400061  1.68599939
+#> 5   30   parent    10.09  9.50814643  0.58185357
+#> 6   62   parent     1.50  0.77966270  0.72033730
+#> 7   90   parent     0.33  0.08739595  0.24260405
+#> 8  118   parent     0.08  0.00979661  0.07020339
+#> 
+#> $atol
+#> [1] 1e-08
+#> 
+#> $rtol
+#> [1] 1e-10
+#> 
+#> $weight.ini
+#> [1] "none"
+#> 
+#> $reweight.tol
+#> [1] 1e-08
+#> 
+#> $reweight.max.iter
+#> [1] 10
+#> 
+#> $bparms.optim
+#>      parent_0 k_parent_sink 
+#>   99.17407218    0.07815759 
+#> 
+#> $bparms.fixed
+#> numeric(0)
+#> 
+#> $bparms.ode
+#> k_parent_sink 
+#>    0.07815759 
+#> 
+#> $bparms.state
+#>   parent 
+#> 99.17407 
+#> 
+#> $date
+#> [1] "Thu Oct  6 09:17:51 2016"
+#> 
+#> attr(,"class")
+#> [1] "mkinfit" "modFit" 
+#> 
+#>

Author

+ + Johannes Ranke + +