[R] Distribution, heteroskedasticity etc. tests for glm, tobit and heckit?
prgosek at gmail.com
Wed May 29 08:29:55 CEST 2013
Is there any package / code snippet to test the distribution
assumption, heteroskedasticity, omitted variables, and linearity with
the models estimated by maximum likelyhood? I especially need it for
three type of models:
* binary choice (probit and probit with non-normal distribution) --
estimated by glm
* tobit and tobit with non-normal distribution -- estimated by AER or
any other suitable package
* heckit and heckit with non-normal distribution
To be more precise, when I estimate e.g. probit model, I should test
that the random part in the data/model is normally distributed. If it
was not, the parameter estimates may be biased. In the help and books
I found how to estimate the parameters but not how to test the
distribution assumption (and other assumptions stated above).
Is there any package or code snippet, or do I need to derive the test
for every distribution and model, and code it myself?
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