Finding the posterior covariance matrix from MATLAB GPR model

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Suhit K
Suhit K 2018-3-16
编辑： Sterling Baird 2021-1-6
I am trying to find the posterior covariance matrix from a gaussian process using MatLab. The GP model is formed as follows:
X = featurevector;
Y = label;
GPMdl = fitrgp(X,Y);
and predicting the mean and variance of test points is as follows:
Xnew = newfeaturevectors;
[PredU,PredS] = predict(Xnew,GPMdl)
PredS only gives me the variance vector of the test points. I want to find the covariance matrix of the test points. Any thoughts on how this can be computed?

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