R: Simulate Parameters from a Theta/Omega specification

rxSimThetaOmega {RxODE} | R Documentation

## Simulate Parameters from a Theta/Omega specification

### Description

Simulate Parameters from a Theta/Omega specification

### Usage

    rxSimThetaOmega(
      params = NULL,
      omega = NULL,
      omegaDf = NULL,
      omegaLower = as.numeric(c(R_NegInf)),
      omegaUpper = as.numeric(c(R_PosInf)),
      omegaIsChol = FALSE,
      nSub = 1L,
      thetaMat = NULL,
      thetaLower = as.numeric(c(R_NegInf)),
      thetaUpper = as.numeric(c(R_PosInf)),
      thetaDf = NULL,
      thetaIsChol = FALSE,
      nStud = 1L,
      sigma = NULL,
      sigmaLower = as.numeric(c(R_NegInf)),
      sigmaUpper = as.numeric(c(R_PosInf)),
      sigmaDf = NULL,
      sigmaIsChol = FALSE,
      nCoresRV = 1L,
      nObs = 1L,
      dfSub = 0,
      dfObs = 0,
      simSubjects = TRUE
    )

### Arguments

`params` | Named Vector of RxODE model parameters
`omega` | Named omega matrix.
`omegaDf` | The degrees of freedom of a t-distribution for simulation. By default this is `NULL` which is equivalent to `Inf` degrees, or to simulate from a normal distribution instead of a t-distribution.
`omegaLower` | Lower bounds for simulated ETAs (by default -Inf)
`omegaUpper` | Upper bounds for simulated ETAs (by default Inf)
`omegaIsChol` | Indicates if the `omega` supplied is a Cholesky decomposed matrix instead of the traditional symmetric matrix.
`nSub` | Number between subject variabilities (ETAs) simulated for every realization of the parameters.
`thetaMat` | Named theta matrix.
`thetaLower` | Lower bounds for simulated population parameter variability (by default -Inf)
`thetaUpper` | Upper bounds for simulated population unexplained variability (by default Inf)
`thetaDf` | The degrees of freedom of a t-distribution for simulation. By default this is `NULL` which is equivalent to `Inf` degrees, or to simulate from a normal distribution instead of a t-distribution.
`thetaIsChol` | Indicates if the `theta` supplied is a Cholesky decomposed matrix instead of the traditional symmetric matrix.
`nStud` | Number virtual studies to characterize uncertainty in estimated parameters.
`sigma` | Matrix for residual variation. Adds a "NA" value for each of the individual parameters, residuals are updated after solve is completed.
`sigmaLower` | Lower bounds for simulated unexplained variability (by default -Inf)
`sigmaUpper` | Upper bounds for simulated unexplained variability (by default Inf)
`sigmaDf` | Degrees of freedom of the sigma t-distribution. By default it is equivalent to `Inf`, or a normal distribution.
`sigmaIsChol` | Boolean indicating if the sigma is in the Cholesky decomposition instead of a symmetric covariance
`nCoresRV` | Number of cores used for the simulation of the sigma variables. By default this is 1. This uses the package `rmvn` and `rmvt`. To reproduce the results you need to run on the same platform with the same number of cores. This is the reason this is set to be one, regardless of what the number of cores are used in threaded ODE solving.
`nObs` | Number of observations to simulate (with `sigma` matrix)
`dfSub` | Degrees of freedom to sample the between subject variability matrix from the inverse Wishart distribution (scaled) or scaled inverse chi squared distribution.
`dfObs` | Degrees of freedom to sample the unexplained variability matrix from the inverse Wishart distribution (scaled) or scaled inverse chi squared distribution.
`simSubjects` | boolean indicated RxODE should simulate subjects in studies (`TRUE`, default) or studies (`FALSE`)

### Author(s)

Matthew L.Fidler

[Package RxODE version 0.9.2-0 Index]