Thank you Simon that's quite helpful! I'll compare that with the GLMSS
models.
Best,
Collin.
>
>> (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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>> PLEASE do read the posting guide
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>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>
> --
> Simon Wood, Mathematical Science, University of Bath BA2 7AY UK
> +44 (0)1225 386603 http://people.bath.ac.uk/sw283
>
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