Sample model parameters from a multivariate normal distribution

This function samples model parameters from NONMEMs covariate matrix (.cov) and final parameter estimates (.ext). Furthermore etas can also be sampled where eta blocks are taken into account (see details)

Usage

sample_par(
  ext,
  covmat = NULL,
  bootstrap = NULL,
  seed = NULL,
  nrepl = 10,
  inc_theta = TRUE,
  inc_eta = FALSE,
  verbose = FALSE,
  dropfixed = FALSE,
  uncert = FALSE,
  restheta = NULL
)

Arguments

ext: character string with location of ext file with final model parameters
covmat: character string with location of cov file with covariance matrix or data.frame of cov file
bootstrap: character string with location of ext files from bootrstrap or vector with ext files from bootstrap (relevant in case ext files should be excluded because of minimization issues)
seed: a numeric with the seed number used in set.seed to enable reproducibility, when not provided the seed from the global environment will be used (e.g. using base::set.seed)
nrepl: numeric with the number of replicates to sample
inc_theta: logical indicating if THETAs should be added to result
inc_eta: logical indicating if ETAs should be added to result
verbose: logical indicating if additional information should be added to result (e.g. OMEGA/SIGMA values)
dropfixed: logical indicating if parameters that are fixed should be dropped (can only be done in case covmat is provided)
uncert: logical indicating if the uncertainty should be sampled
restheta: character with the theta that describes residual error (e.g. "THETA3") in case uncertainty is sampled this parameter will be set to the population value

Value

a dataframe with sampled values

Details

In general the function can be used to sample from covariance matrix so the different parameters can be added to a simulation dataset or model to enable uncertainty simulations. In most cases it is not necessary to include OMEGAs or SIGMAs in these type of simulations. It can be convenient to add ETAs in the simulation dataset to perform a simulation where no $THETA or $OMEGA information is necessary. In case inc_eta is TRUE, the ETAs from the ext files are used and placed in a matrix to take into account covariance or 'BLOCKS'. A matrix from the ext file is constructed based on the naming of OMEGA values (e.g. OMEGA.2.1. will be added to row 2, column 1 and column 1, row 2). The matrix is used as Sigma for the mvrnorm function with mu=0.

Author

Richard Hooijmaijers

Examples


ext <- system.file("example_models","PK.1CMT.ORAL.COV.ext", package = "amp.sim")
cov <- system.file("example_models","PK.1CMT.ORAL.COV.cov", package = "amp.sim")
sample_par(ext, inc_eta = TRUE, nrepl = 5)
#>   ID   STHETA1 STHETA2 STHETA3  STHETA4       SETA1      SETA2
#> 1  1 0.0827885  2.6728 1.58939 0.353994 -0.08900397 -0.1918347
#> 2  2 0.0827885  2.6728 1.58939 0.353994 -0.01041112 -0.3412298
#> 3  3 0.0827885  2.6728 1.58939 0.353994 -0.06753981  0.4407470
#> 4  4 0.0827885  2.6728 1.58939 0.353994  0.10349327  0.1036561
#> 5  5 0.0827885  2.6728 1.58939 0.353994 -0.04793634 -0.1916024
sample_par(ext, cov, uncert = TRUE, nrepl = 5)
#> Warning: Negative values present, take into account when using results within model
#>   ID    STHETA1  STHETA2  STHETA3    STHETA4
#> 1  1 0.07913362 2.568358 1.427934  0.3698506
#> 2  2 0.08071131 2.631000 1.181154 -0.1449949
#> 3  3 0.08442318 2.722236 1.615941  0.5648214
#> 4  4 0.08655393 2.756001 1.692673  0.3736599
#> 5  5 0.08247440 2.739620 1.596263  0.2476445