R/ARIMA.BIC.Order.R

In changepointGA: Changepoint Detection via Modified Genetic Algorithm

#' Calculating BIC for Multiple changepoint detection with model order selection
#'
#' The objective function for changepoint search in Autoregressive
#' moving average with model order selection via Bayesian Information Criterion
#' (BIC).
#'
#' @param chromosome The chromosome consists of the number of changepoints, the
#' order of AR part, the order of MA part, the changepoint locations, and a
#' value of time series length plus 1 (N+1) indicating the end of the chromosome.
#' @param plen The number of model order parameters that need to be selected.
#' If model order selection needs to be performed simultaneously with the
#' changepoint detection task, \code{plen} should be nonzero.
#' @param XMat A matrix contains the covariates, but not includes changepoint
#' effects, for time series regression.
#' @param Xt The simulated ARMA time series from \code{ts.sim} function.
#' @return The BIC value of the objective function.
#' @import stats
#' @importFrom utils tail
#' @useDynLib changepointGA
#' @export
#' @examples
#' N = 1000
#' XMatT = matrix(1, nrow=N, ncol=1)
#' Xt = ts.sim(beta=0.5, XMat=XMatT, sigma=1, phi=0.5, theta=0.8,
#'             Delta=c(2, -2), CpLoc=c(250, 750), seed=1234)
#'
#' # one chromosome representation
#' chromosome = c(2, 1, 1, 250, 750, 1001)
#' ARIMA.BIC.Order(chromosome, plen=2, XMat=XMatT, Xt=Xt)
ARIMA.BIC.Order = function(chromosome, plen=2, XMat, Xt){

  m = chromosome[1]
  p.order = chromosome[2:(plen+1)]
  tau = chromosome[(plen+2):length(chromosome)]
  N = length(Xt) #length of the series

  if(m == 0){
    ##Case 1, Zero Changepoint
    DesignX = XMat
    fit = try(arima(Xt, order = c(p.order[1],0,p.order[2]), xreg=DesignX, include.mean=F,
                    optim.control = list(maxit = 50)))
    if(inherits(fit, "try-error")){
      BIC.obj = NA
    }else{
      BIC.obj = BIC(fit)
    }
  }else{
    tau = tau[tau>1 & tau<N+1] #keep CPT locations only
    tmptau = unique(c(tau, N))
    CpMat = matrix(0, nrow=N, ncol=length(tmptau)-1)
    for(i in 1:NCOL(CpMat)){CpMat[(tmptau[i]+1):tmptau[i+1],i] = 1}
    DesignX = cbind(XMat, CpMat)
    fit = try(arima(Xt, order=c(p.order[1],0,p.order[2]), xreg=DesignX, include.mean=F,
                    optim.control = list(maxit = 50)))
    if(inherits(fit, "try-error")){
      BIC.obj = NA
    }else{
      BIC.obj = BIC(fit)
    }
  }

  return(BIC.obj)
}