Nothing
# This function calculates a distance based on the cross-correlation.
CCorDistance <- function(x, y, lag.max=(min(length(x), length(y)) - 1)){
# Some initial errors are checked
if (is(try(CCInitialCheck(x, y, lag.max)))[1] == "try-error") {
return(NA)
}
# Calculate the correlation between the two series up to the maximum lag,
# if there are no errors.
cc <- ccf(x, y, lag.max=lag.max, type="correlation", plot="FALSE")
# If there are no errors, calculate the distance measure using
# the correlations obtained previously
d <- sqrt((1 - round(cc$acf[, , 1][which(cc$lag == 0)] ^ 2, digits=5)) /
sum(cc$acf[, , 1][which(cc$lag < 0)] ^ 2))
return(d)
}
CCInitialCheck <- function(x, y, lag.max){
if (! is.numeric(x) | ! is.numeric(y)) {
stop('The series must be numeric', call.=FALSE)
}
if (! is.vector(x) | ! is.vector(y)) {
stop('The series must be univariate vectors', call.=FALSE)
}
if (length(x) <= 1 | length(y) <= 1) {
stop('The series must have more than one point', call.=FALSE)
}
if (lag.max < 0) {
stop ('The maximum lag value must be positive', call.=FALSE)
}
if (lag.max >= length(x)) {
stop ('The maximum lag value exceeds the length of the first series', call.=FALSE)
}
if (lag.max >= length(y)) {
stop ('The maximum lag value exceeds the length of the second series', call.=FALSE)
}
if (any(is.na(x)) | any(is.na(y))) {
stop('There are missing values in the series', call.=FALSE)
}
}
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