How do I get proportion of variance?

I have eight variables and I want to know which one is important and I try to use principal component analysis and the one I get is the percentage? The following is my code and I really need proportion not percentage. Thanks in advance.

[COEFF, latent, explained] = pcacov(cov(out)); proportion = cumsum(latent)/sum(latent); figure pareto(latent)

Answer 1

[Nachiket Katakkar]

Your calculation of proportion of variance seems to be correct. The following example highlights that:

% Example from pcacov documentation page
load hald
covx = cov(ingredients);
[COEFF,latent,explained] = pcacov(covx);

cumsum(latent/sum(latent))

ans =

      0.8660
      0.9789
      0.9996
      1.0000

pareto(latent)

You will observe that the pareto chart shows only 95% of the cumulative distribution and therefore, 2 columns will be displayed.

Note also that "pcacov" performs principal components analysis on the covariance matrix of the input so calling "cov" inside "pcacov" does not seem necessary.

[Sonisa]

I got it but I was looking for a way to do proportion of variance with respond to the independent variables to the dependent variables. Is there a way?