R/checkAdmissibility.R

In forecast: Forecasting Functions for Time Series and Linear Models

# Author: srazbash and Rob J Hyndman
###############################################################################

checkAdmissibility <- function(opt.env, box.cox=NULL, small.phi=NULL, ar.coefs=NULL, ma.coefs=NULL, tau=0, bc.lower=0, bc.upper=1) {
  # Check the range of the Box-Cox parameter
  if (!is.null(box.cox)) {
    if ((box.cox <= bc.lower) | (box.cox >= bc.upper)) {
      return(FALSE)
    }
  }
  # Check the range of small.phi
  if (!is.null(small.phi)) {
    if (((small.phi < .8) | (small.phi > 1))) {
      return(FALSE)
    }
  }
  # Check AR part for stationarity
  if (!is.null(ar.coefs)) {
    arlags <- which(abs(ar.coefs) > 1e-08)
    if (length(arlags) > 0L) {
      p <- max(arlags)
      if (min(Mod(polyroot(c(1, -ar.coefs[1L:p])))) < 1 + 1e-2) {
        return(FALSE)
      }
    }
  }
  # Check MA part for invertibility
  if (!is.null(ma.coefs)) {
    malags <- which(abs(ma.coefs) > 1e-08)
    if (length(malags) > 0L) {
      q <- max(malags)
      if (min(Mod(polyroot(c(1, ma.coefs[1L:q])))) < 1 + 1e-2) {
        return(FALSE)
      }
    }
  }
  # Check the eigen values of the D matrix
  D.eigen.values <- eigen(opt.env$D, symmetric = FALSE, only.values = TRUE)$values

  return(all(abs(D.eigen.values) < 1 + 1e-2))
}