oem
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Support observation weights
I noticed that observation weights are not yet supported - are these not simple to incorporate by noticing that weighted least squares minimizes sum( w * (Y - X %% beta)^2 ) = sum_i( (sqrt(w[i]) * X[i, ] %% beta - sqrt(w[i]) * Y[i])^2 ), meaning that one could simulate observation weights simply by multiplying both the design matrix X and the dependent variance Y by sqrt(weights) ?
I haven't had the time to do this but will eventually. There are some tricky issues due to how I scale/standardize the design matrix
I would like to know, if you plan to implement observation weights in the future, or if this isn`t planned anymore?
And, of course, thanks a lot for your package.