diff options
| -rw-r--r-- | NEWS.md | 2 | ||||
| -rw-r--r-- | R/mhmkin.R | 38 | ||||
| -rw-r--r-- | man/mhmkin.Rd | 16 |
3 files changed, 28 insertions, 28 deletions
@@ -1,6 +1,6 @@ # mkin 1.2.2 -- +- 'R/mhmkin.R': Allow an 'illparms.mhmkin' object as value of the argument 'no_random_effects', making it possible to exclude random effects that were ill-defined in simpler variants of the set of degradation models. # mkin 1.2.1 (2022-11-19) @@ -12,13 +12,13 @@ #' degradation models to the same data #' @param backend The backend to be used for fitting. Currently, only saemix is #' supported -#' @param no_random_effect Default is NULL and will be passed to [saem]. If -#' you specify "auto", random effects are only included if the number -#' of datasets in which the parameter passed the t-test is at least 'auto_ranef_threshold'. -#' Beware that while this may make for convenient model reduction or even -#' numerical stability of the algorithm, it will likely lead to -#' underparameterised models. -#' @param auto_ranef_threshold See 'no_random_effect. +#' @param no_random_effect Default is NULL and will be passed to [saem]. If a +#' character vector is supplied, it will be passed to all calls to [saem], +#' regardless if the corresponding parameter is in the model. Alternatively, +#' an object of class [illparms.mhmkin] can be specified. This has to have +#' the same dimensions as the return object of the current call. In this way, +#' ill-defined parameters found in corresponding simpler versions of the +#' degradation model can be specified. #' @param algorithm The algorithm to be used for fitting (currently not used) #' @param \dots Further arguments that will be passed to the nonlinear mixed-effects #' model fitting function. @@ -51,7 +51,7 @@ mhmkin.mmkin <- function(objects, ...) { #' @export #' @rdname mhmkin mhmkin.list <- function(objects, backend = "saemix", algorithm = "saem", - no_random_effect = NULL, auto_ranef_threshold = 3, + no_random_effect = NULL, ..., cores = if (Sys.info()["sysname"] == "Windows") 1 else parallel::detectCores(), cluster = NULL) { @@ -102,22 +102,24 @@ mhmkin.list <- function(objects, backend = "saemix", algorithm = "saem", deg_index <- w[1] error_index <- w[2] mmkin_row <- objects[[error_index]][deg_index, ] - if (identical(no_random_effect, "auto")) { - ip <- illparms(mmkin_row) - ipt <- table(unlist(lapply(as.list(ip), strsplit, ", "))) - no_ranef <- names(ipt)[which((length(ds) - ipt) <= auto_ranef_threshold)] - transparms <- rownames(mmkin_row[[1]]$start_transformed) - bparms <- rownames(mmkin_row[[1]]$start) - names(transparms) <- bparms - no_ranef_trans <- transparms[no_ranef] + if (is(no_random_effect, "illparms.mhmkin")) { + if (identical(dim(no_random_effect), dim(fit_indices))) { + no_ranef_split <- strsplit(no_random_effect[[fit_index]], ", ") + no_ranef <- sapply(no_ranef_split, function(x) { + gsub("sd\\((.*)\\)", "\\1", x) + }) + } else { + stop("Dimensions of illparms.mhmkin object given as 'no_random_effect' are not suitable") + } } else { - no_ranef_trans <- no_random_effect + no_ranef <- no_random_effect } res <- try(do.call(backend_function, - args = c(list(mmkin_row), dot_args, list(no_random_effect = no_ranef_trans)))) + args = c(list(mmkin_row), dot_args, list(no_random_effect = no_ranef)))) return(res) } + fit_time <- system.time({ if (is.null(cluster)) { results <- parallel::mclapply(as.list(1:n.fits), fit_function, diff --git a/man/mhmkin.Rd b/man/mhmkin.Rd index 597fa8ac..4230e44f 100644 --- a/man/mhmkin.Rd +++ b/man/mhmkin.Rd @@ -18,7 +18,6 @@ mhmkin(objects, ...) backend = "saemix", algorithm = "saem", no_random_effect = NULL, - auto_ranef_threshold = 3, ..., cores = if (Sys.info()["sysname"] == "Windows") 1 else parallel::detectCores(), cluster = NULL @@ -42,14 +41,13 @@ supported} \item{algorithm}{The algorithm to be used for fitting (currently not used)} -\item{no_random_effect}{Default is NULL and will be passed to \link{saem}. If -you specify "auto", random effects are only included if the number -of datasets in which the parameter passed the t-test is at least 'auto_ranef_threshold'. -Beware that while this may make for convenient model reduction or even -numerical stability of the algorithm, it will likely lead to -underparameterised models.} - -\item{auto_ranef_threshold}{See 'no_random_effect.} +\item{no_random_effect}{Default is NULL and will be passed to \link{saem}. If a +character vector is supplied, it will be passed to all calls to \link{saem}, +regardless if the corresponding parameter is in the model. Alternatively, +an object of class \link{illparms.mhmkin} can be specified. This has to have +the same dimensions as the return object of the current call. In this way, +ill-defined parameters found in corresponding simpler versions of the +degradation model can be specified.} \item{cores}{The number of cores to be used for multicore processing. This is only used when the \code{cluster} argument is \code{NULL}. On Windows |