Greg Heath <firstname.lastname@example.org> wrote in message <email@example.com>... > I standardize (zero-mean/unit-biased-variance) before calculating > autocorr(x) and > crosscorr(x,y). The results are biased estimates with unity at zero > lag for the autocorrelation. > > To obtain unbiased estimates divide by N-1 instead of N for the > variance and > divide by N-abs(k)-1 instead of N for the kth lag. I didn't like the > resulting plots, > so I use the biased estimate. > > To determine significance levels I averaged over M=100 trials for N = > 100 dimensional Normal Gaussian time series. The 95th average absolute > value was 0.21 and the 100th was 3.1. Therefore I consider correlation > values >= 0.21 as significant. > > A noise-free nth order polynomial can be determined by n+1 points. > Therefore > when I imagine a nth order polynomial fit to a smoothed plot of x, or > y vs x, I start thinking about nonzero lags <= n+1. > > Hope this helps. > > Greg
sigthresh95(N) is a function of N.
I repeated the N=100 experiment for M = 100 and M=1000. I now get