AutoReplicationSettings: Create auto replication settings.
In campsismod: Generic Implementation of a PK/PD Model

AutoReplicationSettings

R Documentation

Create auto replication settings.

Description

By default, all model parameters are sampled from a multivariate normal distribution, whose characteristics are specified by the variance-covariance matrix. OMEGAs and SIGMAs can be sampled from scaled inverse chi-squared or Wishart distributions by setting the wishart argument to TRUE. In that case, THETAs are still sampled from a multivariate normal distribution, while OMEGAS and SIGMAs are sampled from scaled inverse chi-squared (univariate OMEGA/SIGMA distribution) and Wishart (block of OMEGAs/SIGMAs) distribution, respectively. When wishart is set to TRUE, the degrees of freedom of the distribution must be specified, respectively, odf for the OMEGAs and sdf for the SIGMAs.

Usage

AutoReplicationSettings(
  wishart = FALSE,
  odf = NA,
  sdf = NA,
  checkMinMax = TRUE,
  checkPosDef = FALSE,
  quiet = NA
)

Arguments

`wishart`	logical, sample OMEGAs and SIGMAs from scaled inverse chi-squared (univariate OMEGA distribution) or Wishart distribution (block of OMEGAs)
`odf`	the degrees of freedom for the scaled inverse chi-squared/Wishart distribution with regards to the OMEGAs, single integer value (the same degrees of freedom for all OMEGA blocks) or integer vector (one value per OMEGA block)
`sdf`	the degrees of freedom for the scaled inverse chi-squared/Wishart distribution with regards to the SIGMAs, single integer value (the same degrees of freedom for all SIGMA blocks) or integer vector (one value per SIGMA block)
`checkMinMax`	logical, check for min/max values when sampling the parameters, default is TRUE
`checkPosDef`	logical, check for positive definiteness when sampling the OMEGA/SIGMA parameters from the variance-covariance matrix (i.e. when `wishart=FALSE`), default is FALSE (requires extra time)
`quiet`	logical, suppress info messages, default is NA. By default, messages will be printed out when the success rate of sampling the parameters is below 95%.