Residuals from AR1xAR1 one model

I usually think of residuals as being the difference between the observed values and the modeled/fitted values. Residual plots can then be used as diagnostics for the fit of the model.

When I fit a model with an AR1xAR1 spatial structure in the residual covariance matrix, the above philosophy is not quite right. For example, if I look at a heat map/level plot of the residuals, I usually see a smoothish, undulating trend. This is the structure imposed by the correlation of the residuals, and is not structure in the data that that has not been adequately modeled.

There is a resid() function in ASREML-R, but these aren't really deviations from the model in the usual sense, are they?

What is the right way to think about these quantities?

Kevin Wright

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Received on Sat Sep 25 2008 - 19:43:53 EST