Hi,
I am trying to do a PCA analysis on a (24×3333) matrix where 24 is the number of observations and 3333 is the number of variables. I am using:
[coeff,score,eigval] = princomp(zscore(aggregate));
23 PCs are needed to explain 95% of the variance in the data. My question is how do I know which variables are contributing to each component. I believe I need to make a variable spreadsheet naming all 3333 variables. However, it is not clear how I would be able to identify the variables contributing to each component.
I also am creating a variable: %percent variation explained (PVE): variation in the original variable explained by a principal component
Because ultimately I want to quantify how much a variable contributes to its respective principal component.
for i = 1:3333
pve(:,i) = 100*coeff(i,i)*sqrt(var(score(:,i)))/(var(aggregate(:,i)));
end
Any insight would be a big help. I've been trying to figure this out for for weeks with no luck.
Thanks,
Eric
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