From ff83d8b2ba623513d92ac90fac4a1b0ec98c2cb5 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Tue, 5 Oct 2021 17:33:52 +0200 Subject: Update docs --- docs/dev/reference/saem.html | 388 ++----------------------------------------- 1 file changed, 16 insertions(+), 372 deletions(-) (limited to 'docs/dev/reference/saem.html') diff --git a/docs/dev/reference/saem.html b/docs/dev/reference/saem.html index 8d986126..83a62359 100644 --- a/docs/dev/reference/saem.html +++ b/docs/dev/reference/saem.html @@ -287,28 +287,12 @@ using mmkin.

f_mmkin_parent_p0_fixed <- mmkin("FOMC", ds, 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] "Thu Sep 16 14:34:42 2021" -#> .... -#> Minimisation finished -#> [1] "Thu Sep 16 14:34:43 2021"
+
#> Warning: argument is not a function
#>
#> Error in rxModelVars_(obj): Not compatible with STRSXP: [type=NULL].
f_mmkin_parent <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE) f_saem_sfo <- saem(f_mmkin_parent["SFO", ]) -
#> Running main SAEM algorithm -#> [1] "Thu Sep 16 14:34:45 2021" -#> .... -#> Minimisation finished -#> [1] "Thu Sep 16 14:34:47 2021"
f_saem_fomc <- saem(f_mmkin_parent["FOMC", ]) -
#> Running main SAEM algorithm -#> [1] "Thu Sep 16 14:34:47 2021" -#> .... -#> Minimisation finished -#> [1] "Thu Sep 16 14:34:49 2021"
f_saem_dfop <- saem(f_mmkin_parent["DFOP", ]) -
#> Running main SAEM algorithm -#> [1] "Thu Sep 16 14:34:49 2021" -#> .... -#> Minimisation finished -#> [1] "Thu Sep 16 14:34:52 2021"
+
#> Warning: argument is not a function
#>
#> Error in rxModelVars_(obj): Not compatible with STRSXP: [type=NULL].
f_saem_fomc <- saem(f_mmkin_parent["FOMC", ]) +
#> Warning: argument is not a function
#>
#> Error in rxModelVars_(obj): Not compatible with STRSXP: [type=NULL].
f_saem_dfop <- saem(f_mmkin_parent["DFOP", ]) +
#> Warning: argument is not a function
#>
#> Error in rxModelVars_(obj): Not compatible with STRSXP: [type=NULL].
# The returned saem.mmkin object contains an SaemixObject, therefore we can use # functions from saemix library(saemix) @@ -317,53 +301,15 @@ using mmkin.

#> Attaching package: ‘saemix’
#> The following object is masked from ‘package:RxODE’: #> #> phi
compare.saemix(f_saem_sfo$so, f_saem_fomc$so, f_saem_dfop$so) -
#> Likelihoods calculated by importance sampling
#> AIC BIC -#> 1 624.2484 622.2956 -#> 2 467.7096 464.9757 -#> 3 495.4373 491.9222
plot(f_saem_fomc$so, plot.type = "convergence") -
#> Plotting convergence plots
plot(f_saem_fomc$so, plot.type = "individual.fit") -
#> Plotting individual fits
plot(f_saem_fomc$so, plot.type = "npde") -
#> Simulating data using nsim = 1000 simulated datasets -#> Computing WRES and npde . -#> Plotting npde
#> --------------------------------------------- -#> Distribution of npde: -#> mean= -0.01528 (SE= 0.098 ) -#> variance= 0.862 (SE= 0.13 ) -#> skewness= 0.5016 -#> kurtosis= 1.18 -#> --------------------------------------------- -#> -#> Statistical tests -#> Wilcoxon signed rank test : 0.679 -#> Fisher variance test : 0.36 -#> SW test of normality : 0.0855 . -#> Global adjusted p-value : 0.257 -#> --- -#> Signif. codes: '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 -#> ---------------------------------------------
plot(f_saem_fomc$so, plot.type = "vpc") -
#> Performing simulations under the model. -#> Plotting VPC -#> Method used for VPC: binning by quantiles on X , dividing into the following intervals -#> Interval Centered.On -#> 1 (-1,3] 1.3 -#> 2 (3,8] 7.4 -#> 3 (8,14] 13.2 -#> 4 (14,21] 20.5 -#> 5 (21,37.7] 29.5 -#> 6 (37.7,60] 50.4 -#> 7 (60,90] 76.6 -#> 8 (90,120] 109.0 -#> 9 (120,180] 156.0
+
#> Error in compare.saemix(f_saem_sfo$so, f_saem_fomc$so, f_saem_dfop$so): object 'f_saem_sfo' not found
plot(f_saem_fomc$so, plot.type = "convergence") +
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'f_saem_fomc' not found
plot(f_saem_fomc$so, plot.type = "individual.fit") +
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'f_saem_fomc' not found
plot(f_saem_fomc$so, plot.type = "npde") +
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'f_saem_fomc' not found
plot(f_saem_fomc$so, plot.type = "vpc") +
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'f_saem_fomc' not found
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] "Thu Sep 16 14:34:55 2021" -#> .... -#> Minimisation finished -#> [1] "Thu Sep 16 14:35:00 2021"
compare.saemix(f_saem_fomc$so, f_saem_fomc_tc$so) -
#> Likelihoods calculated by importance sampling
#> AIC BIC -#> 1 467.7096 464.9757 -#> 2 469.6831 466.5586
+
#> Warning: argument is not a function
#>
#> Error in rxModelVars_(obj): Not compatible with STRSXP: [type=NULL].
compare.saemix(f_saem_fomc$so, f_saem_fomc_tc$so) +
#> Error in compare.saemix(f_saem_fomc$so, f_saem_fomc_tc$so): object 'f_saem_fomc' not found
sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"), A1 = mkinsub("SFO"))
#> Temporary DLL for differentials generated and loaded
fomc_sfo <- mkinmod(parent = mkinsub("FOMC", "A1"), @@ -380,314 +326,12 @@ using mmkin.

# When using the analytical solutions written for mkin this took around # four minutes f_saem_sfo_sfo <- saem(f_mmkin["SFO-SFO", ]) -
#> Running main SAEM algorithm -#> [1] "Thu Sep 16 14:35:03 2021" -#> .... -#> Minimisation finished -#> [1] "Thu Sep 16 14:35:08 2021"
f_saem_dfop_sfo <- saem(f_mmkin["DFOP-SFO", ]) -
#> Running main SAEM algorithm -#> [1] "Thu Sep 16 14:35:08 2021" -#> .... -#> Minimisation finished -#> [1] "Thu Sep 16 14:35:17 2021"
# We can use print, plot and summary methods to check the results +
#> Warning: argument is not a function
#>
#> Error in rxModelVars_(obj): Not compatible with STRSXP: [type=NULL].
f_saem_dfop_sfo <- saem(f_mmkin["DFOP-SFO", ]) +
#> Warning: argument is not a function
#>
#> Error in rxModelVars_(obj): Not compatible with STRSXP: [type=NULL].
# 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: -#> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * -#> time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) -#> * parent -#> d_A1/dt = + f_parent_to_A1 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g) -#> * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) * -#> exp(-k2 * time))) * parent - k_A1 * A1 -#> -#> Data: -#> 170 observations of 2 variable(s) grouped in 5 datasets -#> -#> Likelihood computed by importance sampling -#> AIC BIC logLik -#> 839.6 834.6 -406.8 -#> -#> Fitted parameters: -#> estimate lower upper -#> parent_0 93.80521 91.22487 96.3856 -#> log_k_A1 -6.06244 -8.26517 -3.8597 -#> f_parent_qlogis -0.97319 -1.37024 -0.5761 -#> log_k1 -2.55394 -4.00815 -1.0997 -#> log_k2 -3.47160 -5.18763 -1.7556 -#> g_qlogis -0.09324 -1.42737 1.2409 -#> Var.parent_0 7.42157 -3.25683 18.1000 -#> Var.log_k_A1 4.22850 -2.46339 10.9204 -#> Var.f_parent_qlogis 0.19803 -0.05541 0.4515 -#> Var.log_k1 2.28644 -0.86079 5.4337 -#> Var.log_k2 3.35626 -1.14639 7.8589 -#> Var.g_qlogis 0.20084 -1.32516 1.7268 -#> a.1 1.88399 1.66794 2.1000 -#> SD.parent_0 2.72425 0.76438 4.6841 -#> SD.log_k_A1 2.05633 0.42919 3.6835 -#> SD.f_parent_qlogis 0.44501 0.16025 0.7298 -#> SD.log_k1 1.51210 0.47142 2.5528 -#> SD.log_k2 1.83201 0.60313 3.0609 -#> SD.g_qlogis 0.44816 -1.25437 2.1507
plot(f_saem_dfop_sfo) -
summary(f_saem_dfop_sfo, data = TRUE) -
#> saemix version used for fitting: 3.1.9000 -#> mkin version used for pre-fitting: 1.1.0 -#> R version used for fitting: 4.1.1 -#> Date of fit: Thu Sep 16 14:35:18 2021 -#> Date of summary: Thu Sep 16 14:35:18 2021 -#> -#> Equations: -#> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * -#> time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) -#> * parent -#> d_A1/dt = + f_parent_to_A1 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g) -#> * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) * -#> exp(-k2 * time))) * parent - k_A1 * A1 -#> -#> Data: -#> 170 observations of 2 variable(s) grouped in 5 datasets -#> -#> Model predictions using solution type analytical -#> -#> Fitted in 9.349 s using 300, 100 iterations -#> -#> Variance model: Constant variance -#> -#> Mean of starting values for individual parameters: -#> parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 -#> 93.8102 -5.3734 -0.9711 -1.8799 -4.2708 -#> g_qlogis -#> 0.1356 -#> -#> Fixed degradation parameter values: -#> None -#> -#> Results: -#> -#> Likelihood computed by importance sampling -#> AIC BIC logLik -#> 839.6 834.6 -406.8 -#> -#> Optimised parameters: -#> est. lower upper -#> parent_0 93.80521 91.225 96.3856 -#> log_k_A1 -6.06244 -8.265 -3.8597 -#> f_parent_qlogis -0.97319 -1.370 -0.5761 -#> log_k1 -2.55394 -4.008 -1.0997 -#> log_k2 -3.47160 -5.188 -1.7556 -#> g_qlogis -0.09324 -1.427 1.2409 -#> -#> Correlation: -#> prnt_0 lg__A1 f_prn_ log_k1 log_k2 -#> log_k_A1 -0.014 -#> f_parent_qlogis -0.025 0.054 -#> log_k1 0.027 -0.003 -0.005 -#> log_k2 0.011 0.005 -0.002 -0.070 -#> g_qlogis -0.067 -0.009 0.011 -0.189 -0.171 -#> -#> Random effects: -#> est. lower upper -#> SD.parent_0 2.7243 0.7644 4.6841 -#> SD.log_k_A1 2.0563 0.4292 3.6835 -#> SD.f_parent_qlogis 0.4450 0.1602 0.7298 -#> SD.log_k1 1.5121 0.4714 2.5528 -#> SD.log_k2 1.8320 0.6031 3.0609 -#> SD.g_qlogis 0.4482 -1.2544 2.1507 -#> -#> Variance model: -#> est. lower upper -#> a.1 1.884 1.668 2.1 -#> -#> Backtransformed parameters: -#> est. lower upper -#> parent_0 93.805214 9.122e+01 96.38556 -#> k_A1 0.002329 2.573e-04 0.02107 -#> f_parent_to_A1 0.274245 2.026e-01 0.35982 -#> k1 0.077775 1.817e-02 0.33296 -#> k2 0.031067 5.585e-03 0.17281 -#> g 0.476707 1.935e-01 0.77572 -#> -#> Resulting formation fractions: -#> ff -#> parent_A1 0.2742 -#> parent_sink 0.7258 -#> -#> Estimated disappearance times: -#> DT50 DT90 DT50back DT50_k1 DT50_k2 -#> parent 13.96 55.4 16.68 8.912 22.31 -#> A1 297.65 988.8 NA NA NA -#> -#> Data: -#> ds name time observed predicted residual std standardized -#> Dataset 6 parent 0 97.2 95.75408 1.445920 1.884 0.767479 -#> Dataset 6 parent 0 96.4 95.75408 0.645920 1.884 0.342847 -#> Dataset 6 parent 3 71.1 71.22466 -0.124662 1.884 -0.066169 -#> Dataset 6 parent 3 69.2 71.22466 -2.024662 1.884 -1.074669 -#> Dataset 6 parent 6 58.1 56.42290 1.677100 1.884 0.890187 -#> Dataset 6 parent 6 56.6 56.42290 0.177100 1.884 0.094003 -#> Dataset 6 parent 10 44.4 44.55255 -0.152554 1.884 -0.080974 -#> Dataset 6 parent 10 43.4 44.55255 -1.152554 1.884 -0.611763 -#> Dataset 6 parent 20 33.3 29.88846 3.411537 1.884 1.810807 -#> Dataset 6 parent 20 29.2 29.88846 -0.688463 1.884 -0.365429 -#> Dataset 6 parent 34 17.6 19.40826 -1.808260 1.884 -0.959805 -#> Dataset 6 parent 34 18.0 19.40826 -1.408260 1.884 -0.747489 -#> Dataset 6 parent 55 10.5 10.45560 0.044398 1.884 0.023566 -#> Dataset 6 parent 55 9.3 10.45560 -1.155602 1.884 -0.613381 -#> Dataset 6 parent 90 4.5 3.74026 0.759744 1.884 0.403264 -#> Dataset 6 parent 90 4.7 3.74026 0.959744 1.884 0.509421 -#> Dataset 6 parent 112 3.0 1.96015 1.039853 1.884 0.551943 -#> Dataset 6 parent 112 3.4 1.96015 1.439853 1.884 0.764258 -#> Dataset 6 parent 132 2.3 1.08940 1.210603 1.884 0.642575 -#> Dataset 6 parent 132 2.7 1.08940 1.610603 1.884 0.854890 -#> Dataset 6 A1 3 4.3 4.75601 -0.456009 1.884 -0.242045 -#> Dataset 6 A1 3 4.6 4.75601 -0.156009 1.884 -0.082808 -#> Dataset 6 A1 6 7.0 7.53839 -0.538391 1.884 -0.285772 -#> Dataset 6 A1 6 7.2 7.53839 -0.338391 1.884 -0.179614 -#> Dataset 6 A1 10 8.2 9.64728 -1.447276 1.884 -0.768198 -#> Dataset 6 A1 10 8.0 9.64728 -1.647276 1.884 -0.874356 -#> Dataset 6 A1 20 11.0 11.83954 -0.839545 1.884 -0.445621 -#> Dataset 6 A1 20 13.7 11.83954 1.860455 1.884 0.987509 -#> Dataset 6 A1 34 11.5 12.81233 -1.312327 1.884 -0.696569 -#> Dataset 6 A1 34 12.7 12.81233 -0.112327 1.884 -0.059622 -#> Dataset 6 A1 55 14.9 12.87919 2.020809 1.884 1.072624 -#> Dataset 6 A1 55 14.5 12.87919 1.620809 1.884 0.860308 -#> Dataset 6 A1 90 12.1 11.52464 0.575364 1.884 0.305397 -#> Dataset 6 A1 90 12.3 11.52464 0.775364 1.884 0.411555 -#> Dataset 6 A1 112 9.9 10.37694 -0.476938 1.884 -0.253153 -#> Dataset 6 A1 112 10.2 10.37694 -0.176938 1.884 -0.093917 -#> Dataset 6 A1 132 8.8 9.32474 -0.524742 1.884 -0.278528 -#> Dataset 6 A1 132 7.8 9.32474 -1.524742 1.884 -0.809317 -#> Dataset 7 parent 0 93.6 90.16918 3.430816 1.884 1.821040 -#> Dataset 7 parent 0 92.3 90.16918 2.130816 1.884 1.131014 -#> Dataset 7 parent 3 87.0 84.05442 2.945583 1.884 1.563483 -#> Dataset 7 parent 3 82.2 84.05442 -1.854417 1.884 -0.984304 -#> Dataset 7 parent 7 74.0 77.00960 -3.009596 1.884 -1.597461 -#> Dataset 7 parent 7 73.9 77.00960 -3.109596 1.884 -1.650540 -#> Dataset 7 parent 14 64.2 67.15684 -2.956840 1.884 -1.569459 -#> Dataset 7 parent 14 69.5 67.15684 2.343160 1.884 1.243724 -#> Dataset 7 parent 30 54.0 52.66290 1.337101 1.884 0.709719 -#> Dataset 7 parent 30 54.6 52.66290 1.937101 1.884 1.028192 -#> Dataset 7 parent 60 41.1 40.04995 1.050050 1.884 0.557355 -#> Dataset 7 parent 60 38.4 40.04995 -1.649950 1.884 -0.875775 -#> Dataset 7 parent 90 32.5 34.09675 -1.596746 1.884 -0.847535 -#> Dataset 7 parent 90 35.5 34.09675 1.403254 1.884 0.744832 -#> Dataset 7 parent 120 28.1 30.12281 -2.022814 1.884 -1.073688 -#> Dataset 7 parent 120 29.0 30.12281 -1.122814 1.884 -0.595977 -#> Dataset 7 parent 180 26.5 24.10888 2.391123 1.884 1.269182 -#> Dataset 7 parent 180 27.6 24.10888 3.491123 1.884 1.853050 -#> Dataset 7 A1 3 3.9 2.77684 1.123161 1.884 0.596161 -#> Dataset 7 A1 3 3.1 2.77684 0.323161 1.884 0.171530 -#> Dataset 7 A1 7 6.9 5.96705 0.932950 1.884 0.495200 -#> Dataset 7 A1 7 6.6 5.96705 0.632950 1.884 0.335963 -#> Dataset 7 A1 14 10.4 10.40535 -0.005348 1.884 -0.002839 -#> Dataset 7 A1 14 8.3 10.40535 -2.105348 1.884 -1.117496 -#> Dataset 7 A1 30 14.4 16.83722 -2.437216 1.884 -1.293648 -#> Dataset 7 A1 30 13.7 16.83722 -3.137216 1.884 -1.665200 -#> Dataset 7 A1 60 22.1 22.15018 -0.050179 1.884 -0.026635 -#> Dataset 7 A1 60 22.3 22.15018 0.149821 1.884 0.079523 -#> Dataset 7 A1 90 27.5 24.36286 3.137143 1.884 1.665161 -#> Dataset 7 A1 90 25.4 24.36286 1.037143 1.884 0.550504 -#> Dataset 7 A1 120 28.0 25.64064 2.359361 1.884 1.252323 -#> Dataset 7 A1 120 26.6 25.64064 0.959361 1.884 0.509218 -#> Dataset 7 A1 180 25.8 27.25486 -1.454858 1.884 -0.772223 -#> Dataset 7 A1 180 25.3 27.25486 -1.954858 1.884 -1.037617 -#> Dataset 8 parent 0 91.9 91.72652 0.173479 1.884 0.092081 -#> Dataset 8 parent 0 90.8 91.72652 -0.926521 1.884 -0.491787 -#> Dataset 8 parent 1 64.9 67.22810 -2.328104 1.884 -1.235732 -#> Dataset 8 parent 1 66.2 67.22810 -1.028104 1.884 -0.545706 -#> Dataset 8 parent 3 43.5 41.46375 2.036251 1.884 1.080820 -#> Dataset 8 parent 3 44.1 41.46375 2.636251 1.884 1.399293 -#> Dataset 8 parent 8 18.3 19.83597 -1.535968 1.884 -0.815275 -#> Dataset 8 parent 8 18.1 19.83597 -1.735968 1.884 -0.921433 -#> Dataset 8 parent 14 10.2 10.34793 -0.147927 1.884 -0.078518 -#> Dataset 8 parent 14 10.8 10.34793 0.452073 1.884 0.239956 -#> Dataset 8 parent 27 4.9 2.67641 2.223595 1.884 1.180260 -#> Dataset 8 parent 27 3.3 2.67641 0.623595 1.884 0.330997 -#> Dataset 8 parent 48 1.6 0.30218 1.297822 1.884 0.688870 -#> Dataset 8 parent 48 1.5 0.30218 1.197822 1.884 0.635791 -#> Dataset 8 parent 70 1.1 0.03075 1.069248 1.884 0.567545 -#> Dataset 8 parent 70 0.9 0.03075 0.869248 1.884 0.461388 -#> Dataset 8 A1 1 9.6 7.74066 1.859342 1.884 0.986918 -#> Dataset 8 A1 1 7.7 7.74066 -0.040658 1.884 -0.021581 -#> Dataset 8 A1 3 15.0 15.37549 -0.375495 1.884 -0.199309 -#> Dataset 8 A1 3 15.1 15.37549 -0.275495 1.884 -0.146230 -#> Dataset 8 A1 8 21.2 19.95900 1.241003 1.884 0.658711 -#> Dataset 8 A1 8 21.1 19.95900 1.141003 1.884 0.605632 -#> Dataset 8 A1 14 19.7 19.92898 -0.228978 1.884 -0.121539 -#> Dataset 8 A1 14 18.9 19.92898 -1.028978 1.884 -0.546170 -#> Dataset 8 A1 27 17.5 16.34046 1.159536 1.884 0.615469 -#> Dataset 8 A1 27 15.9 16.34046 -0.440464 1.884 -0.233793 -#> Dataset 8 A1 48 9.5 10.12131 -0.621313 1.884 -0.329786 -#> Dataset 8 A1 48 9.8 10.12131 -0.321313 1.884 -0.170550 -#> Dataset 8 A1 70 6.2 5.84753 0.352469 1.884 0.187087 -#> Dataset 8 A1 70 6.1 5.84753 0.252469 1.884 0.134008 -#> Dataset 9 parent 0 99.8 98.23600 1.564002 1.884 0.830155 -#> Dataset 9 parent 0 98.3 98.23600 0.064002 1.884 0.033972 -#> Dataset 9 parent 1 77.1 79.68007 -2.580074 1.884 -1.369475 -#> Dataset 9 parent 1 77.2 79.68007 -2.480074 1.884 -1.316396 -#> Dataset 9 parent 3 59.0 55.81142 3.188584 1.884 1.692465 -#> Dataset 9 parent 3 58.1 55.81142 2.288584 1.884 1.214755 -#> Dataset 9 parent 8 27.4 31.81995 -4.419948 1.884 -2.346060 -#> Dataset 9 parent 8 29.2 31.81995 -2.619948 1.884 -1.390640 -#> Dataset 9 parent 14 19.1 22.78328 -3.683282 1.884 -1.955046 -#> Dataset 9 parent 14 29.6 22.78328 6.816718 1.884 3.618240 -#> Dataset 9 parent 27 10.1 14.15172 -4.051720 1.884 -2.150609 -#> Dataset 9 parent 27 18.2 14.15172 4.048280 1.884 2.148783 -#> Dataset 9 parent 48 4.5 6.86094 -2.360941 1.884 -1.253162 -#> Dataset 9 parent 48 9.1 6.86094 2.239059 1.884 1.188468 -#> Dataset 9 parent 70 2.3 3.21580 -0.915798 1.884 -0.486096 -#> Dataset 9 parent 70 2.9 3.21580 -0.315798 1.884 -0.167622 -#> Dataset 9 parent 91 2.0 1.56010 0.439897 1.884 0.233492 -#> Dataset 9 parent 91 1.8 1.56010 0.239897 1.884 0.127335 -#> Dataset 9 parent 120 2.0 0.57458 1.425424 1.884 0.756600 -#> Dataset 9 parent 120 2.2 0.57458 1.625424 1.884 0.862757 -#> Dataset 9 A1 1 4.2 4.01796 0.182037 1.884 0.096623 -#> Dataset 9 A1 1 3.9 4.01796 -0.117963 1.884 -0.062613 -#> Dataset 9 A1 3 7.4 9.08527 -1.685270 1.884 -0.894523 -#> Dataset 9 A1 3 7.9 9.08527 -1.185270 1.884 -0.629129 -#> Dataset 9 A1 8 14.5 13.75054 0.749457 1.884 0.397804 -#> Dataset 9 A1 8 13.7 13.75054 -0.050543 1.884 -0.026827 -#> Dataset 9 A1 14 14.2 14.91180 -0.711804 1.884 -0.377818 -#> Dataset 9 A1 14 12.2 14.91180 -2.711804 1.884 -1.439396 -#> Dataset 9 A1 27 13.7 14.97813 -1.278129 1.884 -0.678417 -#> Dataset 9 A1 27 13.2 14.97813 -1.778129 1.884 -0.943812 -#> Dataset 9 A1 48 13.6 13.75574 -0.155745 1.884 -0.082668 -#> Dataset 9 A1 48 15.4 13.75574 1.644255 1.884 0.872753 -#> Dataset 9 A1 70 10.4 11.92861 -1.528608 1.884 -0.811369 -#> Dataset 9 A1 70 11.6 11.92861 -0.328608 1.884 -0.174422 -#> Dataset 9 A1 91 10.0 10.14395 -0.143947 1.884 -0.076405 -#> Dataset 9 A1 91 9.5 10.14395 -0.643947 1.884 -0.341800 -#> Dataset 9 A1 120 9.1 7.93869 1.161307 1.884 0.616409 -#> Dataset 9 A1 120 9.0 7.93869 1.061307 1.884 0.563330 -#> Dataset 10 parent 0 96.1 93.65914 2.440862 1.884 1.295583 -#> Dataset 10 parent 0 94.3 93.65914 0.640862 1.884 0.340163 -#> Dataset 10 parent 8 73.9 77.83065 -3.930647 1.884 -2.086344 -#> Dataset 10 parent 8 73.9 77.83065 -3.930647 1.884 -2.086344 -#> Dataset 10 parent 14 69.4 70.15862 -0.758619 1.884 -0.402667 -#> Dataset 10 parent 14 73.1 70.15862 2.941381 1.884 1.561253 -#> Dataset 10 parent 21 65.6 64.00840 1.591600 1.884 0.844804 -#> Dataset 10 parent 21 65.3 64.00840 1.291600 1.884 0.685567 -#> Dataset 10 parent 41 55.9 54.71192 1.188076 1.884 0.630618 -#> Dataset 10 parent 41 54.4 54.71192 -0.311924 1.884 -0.165566 -#> Dataset 10 parent 63 47.0 49.66775 -2.667747 1.884 -1.416011 -#> Dataset 10 parent 63 49.3 49.66775 -0.367747 1.884 -0.195196 -#> Dataset 10 parent 91 44.7 45.17119 -0.471186 1.884 -0.250101 -#> Dataset 10 parent 91 46.7 45.17119 1.528814 1.884 0.811478 -#> Dataset 10 parent 120 42.1 41.20430 0.895699 1.884 0.475427 -#> Dataset 10 parent 120 41.3 41.20430 0.095699 1.884 0.050796 -#> Dataset 10 A1 8 3.3 4.00920 -0.709204 1.884 -0.376438 -#> Dataset 10 A1 8 3.4 4.00920 -0.609204 1.884 -0.323359 -#> Dataset 10 A1 14 3.9 5.94267 -2.042668 1.884 -1.084226 -#> Dataset 10 A1 14 2.9 5.94267 -3.042668 1.884 -1.615015 -#> Dataset 10 A1 21 6.4 7.48222 -1.082219 1.884 -0.574430 -#> Dataset 10 A1 21 7.2 7.48222 -0.282219 1.884 -0.149799 -#> Dataset 10 A1 41 9.1 9.76246 -0.662460 1.884 -0.351626 -#> Dataset 10 A1 41 8.5 9.76246 -1.262460 1.884 -0.670100 -#> Dataset 10 A1 63 11.7 10.93972 0.760278 1.884 0.403547 -#> Dataset 10 A1 63 12.0 10.93972 1.060278 1.884 0.562784 -#> Dataset 10 A1 91 13.3 11.93666 1.363337 1.884 0.723645 -#> Dataset 10 A1 91 13.2 11.93666 1.263337 1.884 0.670566 -#> Dataset 10 A1 120 14.3 12.78218 1.517817 1.884 0.805641 -#> Dataset 10 A1 120 12.1 12.78218 -0.682183 1.884 -0.362095
+
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'print': object 'f_saem_dfop_sfo' not found
plot(f_saem_dfop_sfo) +
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'plot': object 'f_saem_dfop_sfo' not found
summary(f_saem_dfop_sfo, data = TRUE) +
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'summary': object 'f_saem_dfop_sfo' not found
# The following takes about 6 minutes #f_saem_dfop_sfo_deSolve <- saem(f_mmkin["DFOP-SFO", ], solution_type = "deSolve", # control = list(nbiter.saemix = c(200, 80), nbdisplay = 10)) -- cgit v1.2.1