diff options
author | Johannes Ranke <jranke@uni-bremen.de> | 2022-11-14 20:03:42 +0100 |
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committer | Johannes Ranke <jranke@uni-bremen.de> | 2022-11-14 20:03:42 +0100 |
commit | 21ad91256dc29423bd905de5c298fd23862b1f3b (patch) | |
tree | 225e2f69ed75b96e5528bcf7b8f25eb3864b75da /R | |
parent | 0db7df4bf632a013099b17d5e817a7dc7146c394 (diff) |
Automatic starting parameters for saem.mmkin
For the case of mkin transformations. This gives faster convergence,
and appears to avoid problems with numeric ODE solutions
Diffstat (limited to 'R')
-rw-r--r-- | R/saem.R | 29 |
1 files changed, 28 insertions, 1 deletions
@@ -37,14 +37,22 @@ utils::globalVariables(c("predicted", "std")) #' @param no_random_effect Character vector of degradation parameters for #' which there should be no variability over the groups. Only used #' if the covariance model is not explicitly specified. -#' @param covariance.model Will be passed to [saemix::SaemixModel()]. Per +#' @param covariance.model Will be passed to [saemix::saemixModel()]. Per #' default, uncorrelated random effects are specified for all degradation #' parameters. +#' @param omega.init Will be passed to [saemix::saemixModel()]. If using +#' mkin transformations and the default covariance model with optionally +#' excluded random effects, the variances of the degradation parameters +#' are estimated using [mean_degparms], with testing of untransformed +#' log parameters for significant difference from zero. If not using +#' mkin transformations or a custom covariance model, the default +#' initialisation of [saemix::saemixModel] is used for omega.init. #' @param covariates A data frame with covariate data for use in #' 'covariate_models', with dataset names as row names. #' @param covariate_models A list containing linear model formulas with one explanatory #' variable, i.e. of the type 'parameter ~ covariate'. Covariates must be available #' in the 'covariates' data frame. +#' @param error.init Will be passed to [saemix::saemixModel()]. #' @param quiet Should we suppress the messages saemix prints at the beginning #' and the end of the optimisation process? #' @param nbiter.saemix Convenience option to increase the number of @@ -136,9 +144,11 @@ saem.mmkin <- function(object, conf.level = 0.6, solution_type = "auto", covariance.model = "auto", + omega.init = "auto", covariates = NULL, covariate_models = NULL, no_random_effect = NULL, + error.init = c(3, 0.1), nbiter.saemix = c(300, 100), control = list(displayProgress = FALSE, print = FALSE, nbiter.saemix = nbiter.saemix, @@ -154,8 +164,10 @@ saem.mmkin <- function(object, solution_type = solution_type, transformations = transformations, covariance.model = covariance.model, + omega.init = omega.init, covariates = covariates, covariate_models = covariate_models, + error.init = error.init, no_random_effect = no_random_effect, ...) d_saemix <- saemix_data(object, covariates = covariates, verbose = verbose) @@ -283,7 +295,9 @@ saemix_model <- function(object, solution_type = "auto", transformations = c("mkin", "saemix"), error_model = "auto", degparms_start = numeric(), covariance.model = "auto", no_random_effect = NULL, + omega.init = "auto", covariates = NULL, covariate_models = NULL, + error.init = numeric(), test_log_parms = FALSE, conf.level = 0.6, verbose = FALSE, ...) { if (nrow(object) > 1) stop("Only row objects allowed") @@ -637,6 +651,18 @@ saemix_model <- function(object, solution_type = "auto", covariance.model = diag(covariance_diagonal) } + if (omega.init[1] == "auto") { + if (transformations == "mkin") { + degparms_eta_ini <- as.numeric( # remove names + mean_degparms(object, + random = TRUE, test_log_parms = TRUE)$eta) + + omega.init <- 2 * diag(degparms_eta_ini^2) + } else { + omega.init <- matrix(nrow = 0, ncol = 0) + } + } + if (is.null(covariate_models)) { covariate.model <- matrix(nrow = 0, ncol = 0) # default in saemixModel() } else { @@ -680,6 +706,7 @@ saemix_model <- function(object, solution_type = "auto", verbose = verbose, covariance.model = covariance.model, covariate.model = covariate.model, + omega.init = omega.init, ... ) attr(res, "mean_dp_start") <- degparms_optim |