pp.timeplot <-
function (x, div="year", type="l", xlab="", xnam=NULL, ...) 
{
	## simple-minded function to plot time series nicely
	## placed in the public domain by Burns Statistics 2010
	##

	if(is.data.frame(x)) x <- as.matrix(x)
	if(is.matrix(x)) {
		matplot(x, axes=FALSE, type=type, xlab=xlab, ...)
		if(!length(xnam)) {
			xnam <- row.names(x)
		} else if(length(xnam) != nrow(x)) {
			stop("'xnam' is the wrong length")
		}
	} else {
		plot(x, axes=FALSE, type=type, xlab=xlab, ...)
		if(!length(xnam)) {
			xnam <- names(x)
		} else if(length(xnam) != length(x)) {
			stop("'xnam' is the wrong length")
		}
	}
	axis(2)
	switch(div,
	  decade={
		tim <- substring(xnam, 1, 3)
		tlab <- paste(unique(tim), "0's", sep="")
	  },
	  year={
		tim <- substring(xnam, 1, 4)
		tlab <- unique(tim)
	  }
	)
	tcount <- cumsum(table(tim))
	tbrk <- tcount[-length(tcount)] + .5
	axis(1, at=tbrk, labels=rep("", length(tbrk)), tck=1, lty=2, col=2)
	axis(1, at=tbrk, labels=rep("", length(tbrk)), lty=2, col=2)
	maxd <- max(diff(tcount))
	# adjust last one if only partial period
	tcount[length(tcount)] <- tcount[length(tcount) - 1] + maxd
	axis(1, at=tcount - maxd/2, labels=tlab, tck=0)
	box()
}