From 91c5db736a4d3f2290a0cc5698fb4e35ae7bda59 Mon Sep 17 00:00:00 2001
From: Johannes Ranke
Date: Wed, 18 May 2022 21:26:17 +0200
Subject: Remove outdated comment in FOCUS L vignette, update docs
This also adds the first benchmark results obtained on my laptop system
---
docs/reference/nlme.mmkin.html | 20 ++++++++++----------
1 file changed, 10 insertions(+), 10 deletions(-)
(limited to 'docs/reference/nlme.mmkin.html')
diff --git a/docs/reference/nlme.mmkin.html b/docs/reference/nlme.mmkin.html
index 1f071ffa..c8bd28e9 100644
--- a/docs/reference/nlme.mmkin.html
+++ b/docs/reference/nlme.mmkin.html
@@ -97,7 +97,7 @@ have been obtained by fitting the same model to a list of datasets.
data = "auto",
fixed = lapply(as.list(names(mean_degparms(model))), function(el) eval(parse(text =
paste(el, 1, sep = "~")))),
- random = pdDiag(fixed),
+ random = pdDiag(fixed),
groups,
start = mean_degparms(model, random = TRUE, test_log_parms = TRUE),
correlation = NULL,
@@ -196,7 +196,7 @@ methods that will automatically work on 'nlme.mmkin' objects, such as
anova(f_nlme_sfo, f_nlme_dfop)
#> Model df AIC BIC logLik Test L.Ratio p-value
#> f_nlme_sfo 1 5 625.0539 637.5529 -307.5269
-#> f_nlme_dfop 2 9 495.1270 517.6253 -238.5635 1 vs 2 137.9269 <.0001
+#> f_nlme_dfop 2 9 495.1270 517.6253 -238.5635 1 vs 2 137.9268 <.0001
print(f_nlme_dfop)
#> Kinetic nonlinear mixed-effects model fit by maximum likelihood
#>
@@ -227,7 +227,7 @@ methods that will automatically work on 'nlme.mmkin' objects, such as
endpoints(f_nlme_dfop)
#> $distimes
#> DT50 DT90 DT50back DT50_k1 DT50_k2
-#> parent 10.79857 100.7937 30.34193 4.193938 43.85443
+#> parent 10.79857 100.7937 30.34192 4.193936 43.85441
#>
ds_2 <- lapply(experimental_data_for_UBA_2019[6:10],
@@ -278,12 +278,12 @@ methods that will automatically work on 'nlme.mmkin' objects, such as
endpoints(f_nlme_dfop_sfo)
#> $ff
#> parent_A1 parent_sink
-#> 0.2768574 0.7231426
+#> 0.2768575 0.7231425
#>
#> $distimes
#> DT50 DT90 DT50back DT50_k1 DT50_k2
#> parent 11.07091 104.6320 31.49737 4.462383 46.20825
-#> A1 162.30519 539.1662 NA NA NA
+#> A1 162.30524 539.1663 NA NA NA
#>
if (length(findFunction("varConstProp")) > 0) { # tc error model for nlme available
@@ -311,7 +311,7 @@ methods that will automatically work on 'nlme.mmkin' objects, such as
#> Fixed effects:
#> list(parent_0 ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1)
#> parent_0 log_k1 log_k2 g_qlogis
-#> 94.04774 -1.82340 -4.16716 0.05686
+#> 94.04775 -1.82340 -4.16715 0.05685
#>
#> Random effects:
#> Formula: list(parent_0 ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1)
@@ -325,7 +325,7 @@ methods that will automatically work on 'nlme.mmkin' objects, such as
#> Formula: ~fitted(.)
#> Parameter estimates:
#> const prop
-#> 2.23223147 0.01262395
+#> 2.23223513 0.01262371
f_2_obs <- update(f_2, error_model = "obs")
f_nlme_sfo_sfo_obs <- nlme(f_2_obs["SFO-SFO", ])
@@ -358,7 +358,7 @@ methods that will automatically work on 'nlme.mmkin' objects, such as
#> Formula: ~1 | name
#> Parameter estimates:
#> parent A1
-#> 1.0000000 0.2049995
+#> 1.0000000 0.2049985
f_nlme_dfop_sfo_obs <- nlme(f_2_obs["DFOP-SFO", ],
control = list(pnlsMaxIter = 120, tolerance = 5e-4))
@@ -370,7 +370,7 @@ methods that will automatically work on 'nlme.mmkin' objects, such as
anova(f_nlme_dfop_sfo, f_nlme_dfop_sfo_obs)
#> Model df AIC BIC logLik Test L.Ratio
#> f_nlme_dfop_sfo 1 13 843.8547 884.6201 -408.9274
-#> f_nlme_dfop_sfo_obs 2 14 817.5338 861.4350 -394.7669 1 vs 2 28.32091
+#> f_nlme_dfop_sfo_obs 2 14 817.5338 861.4350 -394.7669 1 vs 2 28.32092
#> p-value
#> f_nlme_dfop_sfo
#> f_nlme_dfop_sfo_obs <.0001
@@ -390,7 +390,7 @@ methods that will automatically work on 'nlme.mmkin' objects, such as
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