Coudl You please Implement this for me?

for I=1:500 % or any other large number you like
    1. Calculate the autocorrelation function of randn(1,N) where N is the  
       length of the ICE time series
    2. Sort the 2*N-1 absolute values and find the value at index 
       M = floor(0.95*(2*N-1))
    3. Store the value in sigthresh95(I)
end
sigthresh = mean(sigthresh95)

Obtain the autocorrelation function of the ICE time series and find the significant positive lags where abs(autocorrt(N+1:end)) > sigthresh.

I'm new in this area so I'm a true newbie.

I'm looking for a way to get the best lags of a timeserie data using autocorrelation or Partial autocorrelation, that's why I found this answer of yours.

I did not understand the 2*N-1, how the autocorrelation will provide more output than the series itself? You can use any timeseries just to explain.

By the way I become a big fan of your work, and if you have any better way to find the significant lags of a time series I will appreciate very much!

Thank for your attention

[Image Analyst]

Who is the "you" and "yours" you're referring to?

[Alvaro Silvino]

I'm sorry I was in Greg Heath answered questions, and I took this algorithm, so I thought that this question was going directly to him.

[Greg Heath]

The autocorrelation values are calculated by sliding the function through a mirror image of itself: f(t)*f(tau-t). Wikipedia probably has a good visual explanation.

[Greg Heath]

There are many examples of mine posted in the NEWSGROUP and ANSWERS. Search using

 greg narx nncorr

or

greg  narxnet nncorr