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| author | Johannes Ranke <jranke@uni-bremen.de> | 2020-05-26 18:38:51 +0200 |
|---|---|---|
| committer | Johannes Ranke <jranke@uni-bremen.de> | 2020-05-26 18:52:01 +0200 |
| commit | 675a733fa2acc08daabb9b8b571c7d658f281f73 (patch) | |
| tree | ef29cec38aa6d446f7956c0e423cca6bed2e21c0 /R/parms.mkinfit.R | |
| parent | 5e85d8856e7c9db3c52bb6ac5a0a81e2f0c6181c (diff) | |
Use all cores per default, confint tolerance
Also, use more intelligent starting values for the variance of the
random effects for saemix. While this does not appear to speed up
the convergence, it shows where this variance is greatly reduced
by using mixed-effects models as opposed to the separate independent
fits.
Diffstat (limited to 'R/parms.mkinfit.R')
| -rw-r--r-- | R/parms.mkinfit.R | 4 |
1 files changed, 3 insertions, 1 deletions
diff --git a/R/parms.mkinfit.R b/R/parms.mkinfit.R index aae6fa52..a1f2d209 100644 --- a/R/parms.mkinfit.R +++ b/R/parms.mkinfit.R @@ -21,11 +21,13 @@ #' ds <- lapply(experimental_data_for_UBA_2019[6:10], #' function(x) subset(x$data[c("name", "time", "value")])) #' names(ds) <- paste("Dataset", 6:10) -#' fits <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE) +#' \dontrun{ +#' fits <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE, cores = 1) #' parms(fits["SFO", ]) #' parms(fits[, 2]) #' parms(fits) #' parms(fits, transformed = TRUE) +#' } #' @export parms <- function(object, ...) { |