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There is more than certainly forms of regressions that can work on heteroskedastic errors, i.e. non-iid (can be clustering, autoregressive, or more), but part o
by pyromine 10y ago
There is more than certainly forms of regressions that can work on heteroskedastic errors, i.e. non-iid (can be clustering, autoregressive, or more), but part of the general ordinary least squares assumptions and interpretations is iid. errors.
If you do not have iid. errors, any interpretations of the model will be skewed.
There are however other heteroskedasticaly robust interpretations of regressions.
- felixpl 10y agoWeighted least squares should do the trick, i.e. scale your data with the inverse covariance matrix