How to get the least MSE results after cross validation in PLS?

Hi everyone,

I am running a PLS regression and try to select the parameters with lowest MSE, after cross validating, in order to produce a forecasts. Is there any way to retrieve this vector of parameters?

a = randn(100,5); a = zscore(a);
b = randn(100,1); b = zscore(b);

[XL,yl,XS,YS,beta,pctVar,mse,stats] = plsregress(a,b,5,'CV',10);

forecast = [1 a(end,:)]*beta;

But I am not quite sure if these parameters are the optimal.