Hi there, Can someone explain what the difference between spec.pgram and spec.ar is?
I understand that they attempt to do the same thing one using an AR estimation of the underlying series to estimate teh sensity the other using the FFT. However when applied to teh same data set they seem to be giving quite different results? http://r.789695.n4.nabble.com/file/n4541358/R_example.jpg Clearly the spec.ar() result seems to be smoothed but the results are also generally very different only really sharing the peak as the frequencies go towards zero. Can someone please explain why these two functions produce such different results on the same data set? code shown below: library("waveslim") vols=read.csv(file="C:/Users/ocuk/My Documents/Abs Vol.csv", header=TRUE, sep=",") x<-ts(vols[,1]) #x ## LA(8) vol.la8 <- mra(x, "la8", 4, "modwt") names(vol.la8) <- c("d1", "d2", "d3", "d4", "s4") ## plot multiresolution analysis of IBM data #par(mfcol=c(6,1), pty="m", mar=c(5-2,4,4-2,2)) par(mfcol=c(3,1), pty="m", mar=c(5-2,4,4-2,2)) plot.ts(x, axes=F, ylab="", main="(abs rtns)") #for(i in 1:5) # plot.ts(vol.la8[[i]], axes=F, ylab=names(vol.la8)[i]) #axis(side=1, at=seq(0,1600,by=100), # labels=c(0,"",200,"",400,"",600,"",800,"",1000,"",1200,"",1400,"",1600)) spectrum(vol.la8[[1]]) specx <- spec.ar(x) -- View this message in context: http://r.789695.n4.nabble.com/Difference-between-spec-pgram-spec-ar-tp4541358p4541358.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
