acf.plot() question
Have you received a reply to this? I haven't seen one. If not, you might have received a quicker reply if you had noted that the example came from ch. 14 of Venables and Ripley (2002) Modern applied Statistics with S, 4th ed. (Springer, pp. 390-391, to be precise). You ask about the "plot in the lower right-hand corner", which as I read it is labeled "fdeaths". I assume you are asking why the upper-right is labeled "mdeaths and fdeaths" and the lower-left "fdeaths and mdeaths", especially since the lags in the lower left are negative. I agree that it might make more sense, since the lower left lags are negative, to have the label in the lower left the same as in the upper right. However, it doesn't disturb me greatly as it is. spencer graves
DeBarr, Dave wrote:
When I run the "acf()" function using the "acf(ts.union(mdeaths, fdeaths))" example, the "acf()" function calls the "acf.plot()" function to generate this plot... http://members.cox.net/ddebarr/images/acf_example.png The plot in the lower right-hand corner is labeled "fdeaths & mdeaths", but the negative lags appear to belong to "mdeaths & fdeaths" [which correspond to the positive lags of "fdeaths & mdeaths"]. Am I missing something, or should the plot in the lower right-hand corner be labeled "mdeaths & fdeaths" (instead of "fdeaths & mdeaths")? Note: The unit of measure for the lags is years.
autocorrelation <- function(x, y, lags) {
+ n <- length(x)
+ x.bar <- mean(x)
+ y.bar <- mean(y)
+ c <- array(0, length(lags))
+ i <- 1
+ for (t in lags) {
+ s <- seq(max(1, 1 - t), min(n - t, n))
+ c[i] <- sum((x[s + t] - x.bar) * (y[s] - y.bar)) / n
+ i <- i + 1
+ }
+ x.sd <- sqrt(sum((x - x.bar) ^ 2) / n)
+ y.sd <- sqrt(sum((y - y.bar) ^ 2) / n)
+ return(c / (x.sd * y.sd))
+ }
autocorrelation(mdeaths, fdeaths, -15:15)
[1] 0.015054983 0.365626026 0.615427121 0.708206289 0.621895801 [6] 0.340005447 -0.024534195 -0.381671430 -0.611793479 -0.677803477 [11] -0.604031174 -0.349468396 0.019759425 0.405200639 0.744309322 [16] 0.976241251 0.735668532 0.364241839 -0.010675725 -0.382920620 [21] -0.622386979 -0.688538519 -0.610583980 -0.383338305 -0.018112073 [26] 0.391983088 0.656592111 0.721397236 0.639104375 0.361352626 [31] -0.003385423
autocorrelation(fdeaths, mdeaths, -15:15)
[1] -0.003385423 0.361352626 0.639104375 0.721397236 0.656592111 [6] 0.391983088 -0.018112073 -0.383338305 -0.610583980 -0.688538519 [11] -0.622386979 -0.382920620 -0.010675725 0.364241839 0.735668532 [16] 0.976241251 0.744309322 0.405200639 0.019759425 -0.349468396 [21] -0.604031174 -0.677803477 -0.611793479 -0.381671430 -0.024534195 [26] 0.340005447 0.621895801 0.708206289 0.615427121 0.365626026 [31] 0.015054983
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