R/rxCbindStudyIndividual.R

In RxODE: Facilities for Simulating from ODE-Based Models

##' Bind the study parameters and individual parameters
##'
##' @param studyParameters These are the study parameters, often can
##'   be generated by sampling from a population.  This can be either
##'   a matrix or a data frame
##' @param individualParameters A data frame of individual parameters
##' @return Data frame that can be used in RxODE simulations
##' @author Matthew Fidler
##' @examples
##'
##' # Function for coverting coefficient of covariance into a variance
##' lognCv <- function(x){log((x/100)^2+1)}
##'
##' set.seed(32)
##'
##' nSub  <-  100
##' nStud  <-  10
##'
##' #define theta
##' theta <- c(lka=log(0.5), # log ka
##'           lCl=log(5), # log Cl
##'           lV=log(300) # log V
##'           )
##'
##' #define theta Matrix
##' thetaMat <- lotri(lCl ~ lognCv(5),
##'                  lV  ~ lognCv(5),
##'                  lka ~ lognCv(5))
##'
##'
##' nev <- nSub*nStud
##'
##' ev1 <- data.frame(COV1=rnorm(nev,50,30),COV2=rnorm(nev,75,10),
##'                   COV3=sample(c(1.0,2.0),nev,replace=TRUE))
##'
##'
##' tmat <-rxRmvn(nStud, theta[dimnames(thetaMat)[[1]]], thetaMat)
##'
##' rxCbindStudyIndividual(tmat, ev1)
##'
##' @export
rxCbindStudyIndividual <- function(studyParameters, individualParameters) {
  if (!inherits(individualParameters, "data.frame")) {
    stop("'individualParameters' must  be a data frame", call. = FALSE)
  }
  if (inherits(studyParameters, "matrix")) {
    .dimnames <- dimnames(studyParameters)
    if (is.null(.dimnames)) {
      stop("'studyParameters' must be matrix with named columns", call. = FALSE)
    }
    .dimnames <- .dimnames[[2]]
    if (is.null(.dimnames)) {
      stop("'studyParameters' must be matrix with named columns", call. = FALSE)
    }
  } else if (!inherits(studyParameters, "data.frame")) {
    stop("'studyParameters' needs to be either a data frame or a matrix", call. = FALSE)
  }
  .Call(`_rxCbindStudyIndividual`, studyParameters, individualParameters)
}