R/pcmvt.R

In CondMVT: Conditional Multivariate t Distribution, Expectation Maximization Algorithm, and Its Stochastic Variants

pcmvt=function (lower = -Inf, upper = Inf, mean, sigma,df, dependent.ind,
          given.ind, X.given, check.sigma = TRUE, algorithm = GenzBretz(),...)
  {
  #library(mvtnorm)
  if (missing(dependent.ind))
    return("You must specify the indices of dependent random variables in `dependent.ind'")
  if (missing(given.ind) & missing(X.given))
    return(mvtnorm::pmvt(lower = lower, upper = upper, delta = mean[dependent.ind],
                   sigma = as.matrix(sigma[dependent.ind, dependent.ind]),df=df,algorithm =algorithm))
  if (length(X.given) != length(given.ind))
    stop("lengths of `X.given' and `given.ind' must be same")
  ret <- CondMVT(X.given = X.given, mean = mean, sigma = sigma,df=df,
                 dependent.ind = dependent.ind, given.ind = given.ind,
                 check.sigma = check.sigma)
  mvtnorm::pmvt(lower = lower, upper = upper, delta = ret$condMean,
          sigma = ret$condVar,df=ret$cond_df, algorithm = algorithm,...)
}