R/plot.lacv.R

In costat: Time Series Costationarity Determination

plot.lacv <-
function(x, plotcor=TRUE, type="line", lags=0:min(as.integer(10*log10(nrow(x$lacv))),ncol(x$lacv)-1), tcex=1, lcol=1, llty=1, the.time=NULL, ...)
{

nlags <- length(lags)
ntime <- nrow(x$lacv)

if (max(lags)+1 > ncol(x$lacv))
	stop("Maximum lag is too high")

if (length(lcol) == 1)
	lcol <- rep(lcol, length(lags))
if (length(llty) == 1)
	llty <- rep(llty, length(lags))

if (length(lcol) != length(lags))
	stop("Length of lcol vector has to be 1 or the same as the length of the lags vector")

if (length(llty) != length(lags))
	stop("Length of llty vector has to be 1 or the same as the length of the lags vector")

if (type=="line")	{
	if (plotcor==TRUE)	{
		plot(c(1, max(ntime)), c(-1,1), type="n", xlab="Time",
		ylab="ACF", ...)
		for(i in 1:nlags)	{
			lines(1:ntime, x$lacr[, 1+lags[i]], col=lcol[i], lty=llty[i])

			pp <- seq(from=1, to=ntime, length=5)
			text(pp, x$lacr[pp, 1+lags[i]], labels=lags[i], cex=tcex)
		
			}
			
	}
	else
		stop("Line plot for covariance not implemented yet")

}	

else if (type=="persp")	{



	if (plotcor==TRUE)	{
		m <- x$lacr[, lags+1]
		zlab <- "ACF"
		}
	else	{
		m <- x$lacv[, lags+1]
		zlab <- "ACF (cov)"
		}

	persp(x=1:ntime, y=lags, z=m[, lags+1], 
			xlab="Time", ylab="Lag", zlab=zlab, ...)
	}

else if (type=="acf")	{

	if (is.null(the.time))
		stop("You have to specify a time point at which you wish to see the autocovariance/correlation. Specify the.time")

	if (plotcor==TRUE)	{
		acfvals <- x$lacr[the.time,lags+1]
		ylab <- "ACF"
		}
	else	{
		acfvals <- x$lacv[the.time,lags+1]
		ylab <- "ACF (cov)"
		}

	plot(c(0, max(lags)), c(min(acfvals, 0),1), type="n", xlab="Lag", ylab=ylab, ...)
	segments( x0=lags, y0=0, x1=lags, y1=acfvals)
	abline(h=0)

	return(invisible(acfvals))
	}

	



}