How to estimate the Statistical Significance of a Correlation When the Data Are Serially Correlated in matlab?

I want to calculate the statistical significance of a computed correlation coefficient when serial correlation is a concern.

I have two variables (var1 and var2). Data is attached.

I have computed lag correlation between the two time series following the standard procedure. Now I want to check whether estimated the correlation is significant or not using a matlab code.

Looking forward to your valuable suggestions.

For your better understanding on the problem you can refer to this paper

Paper_link

Answer 1

[Scott MacKenzie]

MATLAB's corrcoef function provides the correlation (r) as well as the significance (p) of the correlation. For your data set, the correlation is not significant (p > .05):

M = readmatrix('https://www.mathworks.com/matlabcentral/answers/uploaded_files/930474/DATA.txt');
a = M(:,1);
b = M(:,2);

nanIdx = isnan(a); % seems there are a few nans in a, remove
a = a(~nanIdx);
b = b(~nanIdx);
[r, p] = corrcoef(a,b);

fprintf('r=%.4f, p=%.4f\n', r(1,2), p(1,2));

r=0.0948, p=0.1472

[Subhodh Sharma]

@Scott Lowe Glad to see your response. Your result is not new to me.

I am looking for significance test ( for p value) on my cross correlation analysis.(xcorr in matlab)

That is significance values (p values) of my cross correlations. And am I supposed to do a t-test? or a Z-test? (or any hypothesis test)

I actually need to calculate p-value for Cross-Correlation for two time series ( with my provided data) with delay?

Hope this clears my need.

Thanks to you in advance.

[Scott MacKenzie]

Sorry, not sure.