From 48c463680b51fa767b4cd7bd62865f192d0354ac Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Sat, 6 Feb 2021 18:30:32 +0100 Subject: Reintroduce interface to saemix Also after the upgrade from buster to bullseye of my local system, some test results for saemix have changed. --- docs/dev/reference/saem.html | 56 ++++++++++++++++++++++---------------------- 1 file changed, 28 insertions(+), 28 deletions(-) (limited to 'docs/dev/reference/saem.html') diff --git a/docs/dev/reference/saem.html b/docs/dev/reference/saem.html index 59589378..4578db2a 100644 --- a/docs/dev/reference/saem.html +++ b/docs/dev/reference/saem.html @@ -74,7 +74,7 @@ Expectation Maximisation algorithm (SAEM)." /> mkin - 0.9.50.4 + 1.0.1.9000 @@ -261,27 +261,27 @@ using mmkin.

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] "Mon Jan 25 14:41:42 2021" +#> [1] "Sat Feb 6 18:29:26 2021" #> .... #> Minimisation finished -#> [1] "Mon Jan 25 14:41:43 2021"
+#> [1] "Sat Feb 6 18:29:27 2021"
f_mmkin_parent <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE) f_saem_sfo <- saem(f_mmkin_parent["SFO", ])
#> Running main SAEM algorithm -#> [1] "Mon Jan 25 14:41:45 2021" +#> [1] "Sat Feb 6 18:29:28 2021" #> .... #> Minimisation finished -#> [1] "Mon Jan 25 14:41:46 2021"
f_saem_fomc <- saem(f_mmkin_parent["FOMC", ]) +#> [1] "Sat Feb 6 18:29:30 2021"
f_saem_fomc <- saem(f_mmkin_parent["FOMC", ])
#> Running main SAEM algorithm -#> [1] "Mon Jan 25 14:41:47 2021" +#> [1] "Sat Feb 6 18:29:30 2021" #> .... #> Minimisation finished -#> [1] "Mon Jan 25 14:41:49 2021"
f_saem_dfop <- saem(f_mmkin_parent["DFOP", ]) +#> [1] "Sat Feb 6 18:29:32 2021"
f_saem_dfop <- saem(f_mmkin_parent["DFOP", ])
#> Running main SAEM algorithm -#> [1] "Mon Jan 25 14:41:49 2021" +#> [1] "Sat Feb 6 18:29:32 2021" #> .... #> Minimisation finished -#> [1] "Mon Jan 25 14:41:52 2021"
+#> [1] "Sat Feb 6 18:29:35 2021"
# The returned saem.mmkin object contains an SaemixObject, therefore we can use # functions from saemix library(saemix) @@ -324,10 +324,10 @@ using mmkin.

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] "Mon Jan 25 14:41:55 2021" +#> [1] "Sat Feb 6 18:29:37 2021" #> .... #> Minimisation finished -#> [1] "Mon Jan 25 14:42:00 2021"
compare.saemix(list(f_saem_fomc$so, f_saem_fomc_tc$so)) +#> [1] "Sat Feb 6 18:29:42 2021"
compare.saemix(list(f_saem_fomc$so, f_saem_fomc_tc$so))
#> Error in compare.saemix(list(f_saem_fomc$so, f_saem_fomc_tc$so)): 'compare.saemix' requires at least two models.
sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"), A1 = mkinsub("SFO")) @@ -346,15 +346,15 @@ using mmkin.

# four minutes f_saem_sfo_sfo <- saem(f_mmkin["SFO-SFO", ])
#> Running main SAEM algorithm -#> [1] "Mon Jan 25 14:42:02 2021" +#> [1] "Sat Feb 6 18:29:44 2021" #> .... #> Minimisation finished -#> [1] "Mon Jan 25 14:42:07 2021"
f_saem_dfop_sfo <- saem(f_mmkin["DFOP-SFO", ]) +#> [1] "Sat Feb 6 18:29:48 2021"
f_saem_dfop_sfo <- saem(f_mmkin["DFOP-SFO", ])
#> Running main SAEM algorithm -#> [1] "Mon Jan 25 14:42:08 2021" +#> [1] "Sat Feb 6 18:29:49 2021" #> .... #> Minimisation finished -#> [1] "Mon Jan 25 14:42:17 2021"
# We can use print, plot and summary methods to check the results +#> [1] "Sat Feb 6 18:29:57 2021"
# 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: @@ -395,10 +395,10 @@ using mmkin.

#> SD.g_qlogis 0.44771 -0.86417 1.7596
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: 0.9.50.4 +#> mkin version used for pre-fitting: 1.0.1.9000 #> R version used for fitting: 4.0.3 -#> Date of fit: Mon Jan 25 14:42:18 2021 -#> Date of summary: Mon Jan 25 14:42:18 2021 +#> Date of fit: Sat Feb 6 18:29:57 2021 +#> Date of summary: Sat Feb 6 18:29:58 2021 #> #> Equations: #> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -413,7 +413,7 @@ using mmkin.

#> #> Model predictions using solution type analytical #> -#> Fitted in 9.954 s using 300, 100 iterations +#> Fitted in 8.539 s using 300, 100 iterations #> #> Variance model: Constant variance #> @@ -489,12 +489,12 @@ using mmkin.

#> Dataset 6 parent 3 69.2 71.32042 2.12042 1.883 1.125873 #> Dataset 6 parent 6 58.1 56.45256 -1.64744 1.883 -0.874739 #> Dataset 6 parent 6 56.6 56.45256 -0.14744 1.883 -0.078288 -#> Dataset 6 parent 10 44.4 44.48523 0.08523 1.883 0.045256 +#> Dataset 6 parent 10 44.4 44.48523 0.08523 1.883 0.045257 #> Dataset 6 parent 10 43.4 44.48523 1.08523 1.883 0.576224 #> Dataset 6 parent 20 33.3 29.75774 -3.54226 1.883 -1.880826 #> Dataset 6 parent 20 29.2 29.75774 0.55774 1.883 0.296141 #> Dataset 6 parent 34 17.6 19.35710 1.75710 1.883 0.932966 -#> Dataset 6 parent 34 18.0 19.35710 1.35710 1.883 0.720578 +#> Dataset 6 parent 34 18.0 19.35710 1.35710 1.883 0.720579 #> Dataset 6 parent 55 10.5 10.48443 -0.01557 1.883 -0.008266 #> Dataset 6 parent 55 9.3 10.48443 1.18443 1.883 0.628895 #> Dataset 6 parent 90 4.5 3.78622 -0.71378 1.883 -0.378995 @@ -560,9 +560,9 @@ using mmkin.

#> Dataset 8 parent 1 64.9 67.73197 2.83197 1.883 1.503686 #> Dataset 8 parent 1 66.2 67.73197 1.53197 1.883 0.813428 #> Dataset 8 parent 3 43.5 41.58448 -1.91552 1.883 -1.017081 -#> Dataset 8 parent 3 44.1 41.58448 -2.51552 1.883 -1.335661 +#> Dataset 8 parent 3 44.1 41.58448 -2.51552 1.883 -1.335662 #> Dataset 8 parent 8 18.3 19.62286 1.32286 1.883 0.702395 -#> Dataset 8 parent 8 18.1 19.62286 1.52286 1.883 0.808589 +#> Dataset 8 parent 8 18.1 19.62286 1.52286 1.883 0.808588 #> Dataset 8 parent 14 10.2 10.77819 0.57819 1.883 0.306999 #> Dataset 8 parent 14 10.8 10.77819 -0.02181 1.883 -0.011582 #> Dataset 8 parent 27 4.9 3.26977 -1.63023 1.883 -0.865599 @@ -575,13 +575,13 @@ using mmkin.

#> Dataset 8 A1 1 7.7 7.61539 -0.08461 1.883 -0.044923 #> Dataset 8 A1 3 15.0 15.47954 0.47954 1.883 0.254622 #> Dataset 8 A1 3 15.1 15.47954 0.37954 1.883 0.201525 -#> Dataset 8 A1 8 21.2 20.22616 -0.97384 1.883 -0.517076 +#> Dataset 8 A1 8 21.2 20.22616 -0.97384 1.883 -0.517075 #> Dataset 8 A1 8 21.1 20.22616 -0.87384 1.883 -0.463979 #> Dataset 8 A1 14 19.7 20.00067 0.30067 1.883 0.159645 #> Dataset 8 A1 14 18.9 20.00067 1.10067 1.883 0.584419 -#> Dataset 8 A1 27 17.5 16.38142 -1.11858 1.883 -0.593929 -#> Dataset 8 A1 27 15.9 16.38142 0.48142 1.883 0.255619 -#> Dataset 8 A1 48 9.5 10.25357 0.75357 1.883 0.400123 +#> Dataset 8 A1 27 17.5 16.38142 -1.11858 1.883 -0.593928 +#> Dataset 8 A1 27 15.9 16.38142 0.48142 1.883 0.255620 +#> Dataset 8 A1 48 9.5 10.25357 0.75357 1.883 0.400124 #> Dataset 8 A1 48 9.8 10.25357 0.45357 1.883 0.240833 #> Dataset 8 A1 70 6.2 5.95728 -0.24272 1.883 -0.128878 #> Dataset 8 A1 70 6.1 5.95728 -0.14272 1.883 -0.075781 @@ -622,7 +622,7 @@ using mmkin.

#> Dataset 9 A1 91 10.0 10.09177 0.09177 1.883 0.048727 #> Dataset 9 A1 91 9.5 10.09177 0.59177 1.883 0.314211 #> Dataset 9 A1 120 9.1 7.91379 -1.18621 1.883 -0.629841 -#> Dataset 9 A1 120 9.0 7.91379 -1.08621 1.883 -0.576745 +#> Dataset 9 A1 120 9.0 7.91379 -1.08621 1.883 -0.576744 #> Dataset 10 parent 0 96.1 93.65257 -2.44743 1.883 -1.299505 #> Dataset 10 parent 0 94.3 93.65257 -0.64743 1.883 -0.343763 #> Dataset 10 parent 8 73.9 77.85906 3.95906 1.883 2.102132 -- cgit v1.2.1