From 137612045c23198f10d6e8612c32e266c2a6c00e Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 29 Jul 2021 12:17:56 +0200 Subject: Go back to 1.0.x version, update docs --- docs/dev/reference/saem.html | 38 +++++++++++++++++++------------------- 1 file changed, 19 insertions(+), 19 deletions(-) (limited to 'docs/dev/reference/saem.html') diff --git a/docs/dev/reference/saem.html b/docs/dev/reference/saem.html index 15271c8a..0334e0e1 100644 --- a/docs/dev/reference/saem.html +++ b/docs/dev/reference/saem.html @@ -74,7 +74,7 @@ Expectation Maximisation algorithm (SAEM)." /> mkin - 1.1.0 + 1.0.5 @@ -288,27 +288,27 @@ 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] "Tue Jul 27 16:31:02 2021" +#> [1] "Thu Jul 29 12:14:07 2021" #> .... #> Minimisation finished -#> [1] "Tue Jul 27 16:31:04 2021"
+#> [1] "Thu Jul 29 12:14:08 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] "Tue Jul 27 16:31:06 2021" +#> [1] "Thu Jul 29 12:14:11 2021" #> .... #> Minimisation finished -#> [1] "Tue Jul 27 16:31:07 2021"
f_saem_fomc <- saem(f_mmkin_parent["FOMC", ]) +#> [1] "Thu Jul 29 12:14:12 2021"
f_saem_fomc <- saem(f_mmkin_parent["FOMC", ])
#> Running main SAEM algorithm -#> [1] "Tue Jul 27 16:31:07 2021" +#> [1] "Thu Jul 29 12:14:12 2021" #> .... #> Minimisation finished -#> [1] "Tue Jul 27 16:31:09 2021"
f_saem_dfop <- saem(f_mmkin_parent["DFOP", ]) +#> [1] "Thu Jul 29 12:14:14 2021"
f_saem_dfop <- saem(f_mmkin_parent["DFOP", ])
#> Running main SAEM algorithm -#> [1] "Tue Jul 27 16:31:10 2021" +#> [1] "Thu Jul 29 12:14:15 2021" #> .... #> Minimisation finished -#> [1] "Tue Jul 27 16:31:12 2021"
+#> [1] "Thu Jul 29 12:14:18 2021"
# The returned saem.mmkin object contains an SaemixObject, therefore we can use # functions from saemix library(saemix) @@ -357,10 +357,10 @@ 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] "Tue Jul 27 16:31:16 2021" +#> [1] "Thu Jul 29 12:14:21 2021" #> .... #> Minimisation finished -#> [1] "Tue Jul 27 16:31:20 2021"
compare.saemix(f_saem_fomc$so, f_saem_fomc_tc$so) +#> [1] "Thu Jul 29 12:14:27 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
@@ -381,15 +381,15 @@ using mmkin.

# four minutes f_saem_sfo_sfo <- saem(f_mmkin["SFO-SFO", ])
#> Running main SAEM algorithm -#> [1] "Tue Jul 27 16:31:24 2021" +#> [1] "Thu Jul 29 12:14:31 2021" #> .... #> Minimisation finished -#> [1] "Tue Jul 27 16:31:29 2021"
f_saem_dfop_sfo <- saem(f_mmkin["DFOP-SFO", ]) +#> [1] "Thu Jul 29 12:14:36 2021"
f_saem_dfop_sfo <- saem(f_mmkin["DFOP-SFO", ])
#> Running main SAEM algorithm -#> [1] "Tue Jul 27 16:31:30 2021" +#> [1] "Thu Jul 29 12:14:36 2021" #> .... #> Minimisation finished -#> [1] "Tue Jul 27 16:31:38 2021"
# We can use print, plot and summary methods to check the results +#> [1] "Thu Jul 29 12:14:46 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: @@ -430,10 +430,10 @@ using mmkin.

#> 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 +#> mkin version used for pre-fitting: 1.0.5 #> R version used for fitting: 4.1.0 -#> Date of fit: Tue Jul 27 16:31:39 2021 -#> Date of summary: Tue Jul 27 16:31:39 2021 +#> Date of fit: Thu Jul 29 12:14:46 2021 +#> Date of summary: Thu Jul 29 12:14:46 2021 #> #> Equations: #> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -448,7 +448,7 @@ using mmkin.

#> #> Model predictions using solution type analytical #> -#> Fitted in 9.479 s using 300, 100 iterations +#> Fitted in 9.987 s using 300, 100 iterations #> #> Variance model: Constant variance #> -- cgit v1.2.1