How to obtain trend p-values for each cell of a matrix?

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Hello,
I am trying to output the regression p-values for each cell separately. I've successfully calculated the regression coefficients for each cell using polyfit:
for i=1:695
for j=1:822
summer_trend(1:2,i,j)=polyfit(year,summer(:,i,j),1);
end
end
However, I would now like to obtain the p-values for the coefficients cell-by-cell. Normally, I would use regstats and select tstat.pval but I'm not sure how to apply this over a matrix. I've tried for example the following code but the problem I have is the functions I've found always return a structure (which is no good when I have a matrix instead of vector...):
for i=1:695
for j=1:822
summer_pval=regstats(summer(:,i,j),year, 'linear',{'tstat'});
end
end
Any ideas how I could do this? Many thanks!

Answers (1)

Tom Lane
Tom Lane on 12 Apr 2013
You are right that regstats returns a structure, but it contains numeric values that you can assign into a matrix. For example, something like this:
s = regstats(pop,cdate,'linear');
coefmat(1:2,1) = s.tstat.beta;
pvalmat(1:2,1) = s.tstat.pval;
  2 Comments
Anna
Anna on 12 Apr 2013
Hi Tom, Thanks for your reply. However, I'm still not sure how to apply this over a matrix. I can't use my [695X822] matrix as the y input of regstats(y,x), as in your example, as that returns the error "RESPONSES must have a single column".
The loop above that I tried using on the other hand returns the error "The design matrix has more predictor variables than observations".
Would you be able to explain how this can be done cell-by-cell using a matrix (as opposed to a vector column) as the y variable? Thanks
Tom Lane
Tom Lane on 13 Apr 2013
I had in mind this modification of your code:
for i=1:695
for j=1:822
s = regstats(summer(:,i,j),year);
summer_trend(1:2,i,j) = s.tstat.beta;
summer_pval(1:2,i,j) = s.tstat.pval;
end
end

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