Compute log likelihood after fitting the GLM?
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I am playing around with a toy general linear model (GLM) with MATLAB glmfit.
X=[1;2;3;4];
y=[1.1;2.2;3.5;4.9];
[b, dev, stats] = glmfit(X, y);
How should I compute the log likelihood of the data? I want to do
y_fit = glmval(b, X, 'identity');
ll = nansum(log(normpdf(y, y_fit, sigma)));
But how to find sigma, the standard deviation of the Gaussian?
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