From 1ef7008be2a72a0847064ad9c2ddcfa16b055482 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Fri, 3 May 2019 19:14:15 +0200 Subject: Improve error model fitting Now we have a three stage fitting process for nonconstant error models: - Unweighted least squares - Only optimize the error model - Optimize both Static documentation rebuilt by pkgdown --- docs/reference/mkinparplot.html | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) (limited to 'docs/reference/mkinparplot.html') diff --git a/docs/reference/mkinparplot.html b/docs/reference/mkinparplot.html index c90acf4a..8cfb9374 100644 --- a/docs/reference/mkinparplot.html +++ b/docs/reference/mkinparplot.html @@ -154,8 +154,7 @@ 
model <- mkinmod(
   T245 = mkinsub("SFO", to = c("phenol"), sink = FALSE),
   phenol = mkinsub("SFO", to = c("anisole")),
-  anisole = mkinsub("SFO"), use_of_ff = "max")
#> Successfully compiled differential equation model from auto-generated C code.
fit <- mkinfit(model, subset(mccall81_245T, soil == "Commerce"), quiet = TRUE)
#> Warning: Observations with value of zero were removed from the data
#> Warning: Optimisation did not converge:
-#> false convergence (8)
mkinparplot(fit)
+ anisole = mkinsub("SFO"), use_of_ff = "max")
#> Successfully compiled differential equation model from auto-generated C code.
fit <- mkinfit(model, subset(mccall81_245T, soil == "Commerce"), quiet = TRUE)
#> Warning: Observations with value of zero were removed from the data
mkinparplot(fit)