(1) Am I correct in understanding that Heteroscedasticity is a problem for
Generalized Additive Models as it is for standard linear models? I am
asking particularly about the GAMs as implemented in the mgcv package.
Based upon my online search it seems that some forms of penalized splines
can address heteroscedasticity while others cannot and I'm not sure what
is true of the methods used in mgcv.
- Yes, the mgcv implementation estimates the models via penalized
likelihood maximisation, and will be as sensitive to violation of the
assumed mean variance relationship as any GLM fitted by MLE.
(2) Assuming that heteroscedasticity is a problem for the mgcv GAMs, can
anyone recommend a good test implementation? I am familiar with the
ncvTest method implemented in the car package but that applies only to
lms.
- I tend to check for heteroscedasticity graphically using the usual
plots of residuals vs fitted values, predictors (and possibly
combinations of predictors). I like the way that plots often point
towards a solution to any problem they show.
best,
Simon
Thank you,
Collin Lynch.
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Simon Wood, Mathematical Science, University of Bath BA2 7AY UK
+44 (0)1225 386603 http://people.bath.ac.uk/sw283
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