In JMP Pro 11, we introduced the Fit Mixed platform for fitting models with a variety of covariance structures and random effects. With JMP Pro 12, we have improved on this platform, with noticeable changes coming to models with spatial covariance structures. These changes are detailed below. Enhanced speed Fitting
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Coming in JMP Pro 12: Variograms in Fit Mixed
Variable clustering in JMP
When presented with a large number of variables to predict an outcome, you may want to reduce the number of variables in some way to make the prediction problem easier to tackle. One possible dimension reduction technique is the well-known method of principal components analysis (PCA). The variables resulting from