Nothing
ADCFplot <- function(x, MaxLag = 15, alpha = 0.05, b = 499, bootMethod =
c("Wild Bootstrap", "Subsampling", "Independent Bootstrap"), ylim = NULL, main = NULL) {
if ( b <= 0 ) stop( "No plot is given for b<=0." )
if ( MaxLag == 0 ) stop( "MaxLag must be greater than 0." )
series <- deparse( substitute(x) )
bootMethod <- match.arg(bootMethod)
if ( missing(bootMethod) ) bootMethod <- "Wild Bootstrap"
n <- length(x)
adcor <- ADCF(x, MaxLag, unbiased = FALSE)
if ( bootMethod == "Wild Bootstrap" ) {
cv <- RbootCV(n, MaxLag, alpha, b, parallel = TRUE)
} else if ( bootMethod == "Independent Bootstrap" ) {
cv <- OrdinaryBootCV(n, MaxLag, alpha, b, parallel = TRUE)
} else {
if ( ( (n - MaxLag) < 0 ) || ( (n - MaxLag) < 4 ) || ( (n - MaxLag) <= 25 ) ) stop( "Give bigger sample size n." )
cv <- SubsCV(x, MaxLag, alpha, parallel = TRUE)
}
r1 <- max(cv, 1)
if ( is.null(ylim) ) ylim <- c(0, r1)
if ( length(cv) == 1 ) {
if ( is.null(main) ) {
plot(0:MaxLag, adcor, type = "n", main = paste("Series", series), xlab = "Lag",
ylab = "ADCF", ylim = ylim, cex.lab = 1.2, cex.axis = 1.2)
} else plot(0:MaxLag, adcor, type = "n", main = main, xlab = "Lag", ylab = "ADCF",
ylim = ylim, cex.lab = 1.2, cex.axis = 1.2)
for ( i in seq(0, MaxLag, by = 1) ) segments(i, 0, i, adcor[i + 1])
points(0:MaxLag, rep(cv, MaxLag + 1), type = "l", lty = 3, lwd = 2, col = "blue")
} else {
if ( is.null(main) ) {
plot(1:MaxLag, adcor[-1], type = "n", main = paste("Series", series), xlab = "Lag",
ylab = "ADCF", ylim = ylim, cex.lab = 1.2, cex.axis = 1.2)
} else plot(1:MaxLag, adcor[-1], type = "n", main = main, xlab = "Lag", ylab = "ADCF",
ylim = ylim, cex.lab = 1.2, cex.axis = 1.2)
for ( i in seq(1, MaxLag, by = 1) ) segments(i, 0, i, adcor[i + 1])
points(1:MaxLag, cv, type = "l", lty = 3, lwd = 2, col = "blue")
}
result <- list(ADCF = adcor, bootMethod = bootMethod, critical.values = cv)
return(result)
}
# ADCFplot <- function (x, MaxLag = 15, ylim=NULL, main = NULL, bootMethod = c("Wild Bootstrap",
# "Subsampling","Independent Bootstrap"), b = 499)
# {
# if (b <= 0)
# stop("No plot is given for b<=0")
# if (MaxLag==0)
# stop("MaxLag must be greater than 0")
# series <- deparse(substitute(x))
# bootMethod <- match.arg(bootMethod)
# if (missing(bootMethod))
# bootMethod = "Wild Bootstrap"
# n <- length(x)
# adcor <- ADCF(x, MaxLag, unbiased=FALSE)
# if (bootMethod == "Wild Bootstrap") {
# cv <- RbootCV(n, MaxLag, b = b, parallel = TRUE)
# }
# else if (bootMethod == "Independent Bootstrap") {
# cv <- OrdinaryBootCV(n, MaxLag, b = b, parallel = TRUE)
# }
# else {
# if (((n - MaxLag) < 0) || ((n - MaxLag) < 4) || ((n -
# MaxLag) <= 25))
# stop("Give bigger sample size n")
# cv <- SubsCV(x,MaxLag,parallel=TRUE)
# }
# r1 <- max(cv, 1)
# if (is.null(ylim)) ylim=c(0,r1)
# if (length(cv) == 1) {
# if (is.null(main)) {
# plot(0:MaxLag, adcor, type = "n", main = paste("Series",
# series), xlab = "Lag", ylab = "ADCF", ylim = ylim)
# }
# else {
# plot(0:MaxLag, adcor, type = "n", main = main, xlab = "Lag",
# ylab = "ADCF", ylim = ylim)
# }
# for (i in seq(0, MaxLag, by = 1)) {
# segments(i, 0, i, adcor[i + 1])
# }
# points(0:MaxLag, rep(cv, MaxLag + 1), type = "l", lty = 3,
# lwd = 2, col = "blue")
# }
# else {
# if (is.null(main)) {
# plot(1:MaxLag, adcor[-1], type = "n", main = paste("Series",
# series), xlab = "Lag", ylab = "ADCF", ylim = ylim)
# }
# else {
# plot(1:MaxLag, adcor[-1], type = "n", main = main,
# xlab = "Lag", ylab = "ADCF", ylim = ylim)
# }
# for (i in seq(1, MaxLag, by = 1)) {
# segments(i, 0, i, adcor[i + 1])
# }
# points(1:MaxLag, cv, type = "l", lty = 3, lwd = 2, col = "blue")
# }
# result <- list(ADCF = adcor, bootMethod = bootMethod, critical.values = cv)
# return(result)
# }
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