R/detectIO.R

In TSA: Time Series Analysis

#' @export 
detectIO <-
function (object,alpha=0.05,robust=TRUE) 
{
# programmed by Kung-Sik Chan
# date: May 5, 2006
#
# This function serves to detect whether there is any IO. It implements the
# test statistic lambda_{1,t} proposed by Chang, Chen and Tiao (1988).
#
# input: 
#       object=an ARMA model
#       alpha=family significance level (5% is the default)
#             Bonferroni rule is used to control the family error rate.
#       robust=if true, the noise standard deviation is estimated by
#               mean absolute residuals times sqrt(pi/2). Otherwise,
#               it is the estimated by sqrt(sigma2) from the arima fit.
# side effects: print the test statistics of the found IO and their time indices.
#
# output:
#        a list containing the time indices, named ind, and the test statistics of the found
#        IO, named lambda1
#
#

resid=residuals(object)
if(robust) sigma=sqrt(pi/2)*mean(abs(resid),na.rm=TRUE) else sigma=object$sigma2^.5
lambda1T=resid/sigma
cutoff=qnorm(1-alpha/2/length(lambda1T))
out=abs(lambda1T)>cutoff
ind=seq(lambda1T)[out]
lambda1=lambda1T[out]
if(length(ind)>0) print(rbind(ind, lambda1)) else print("No IO detected")
invisible(list(lambda1=lambda1,ind=ind))
}