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If we have misspecification in the form of simple under/overdispersion, like in GLM or Poisson model with scale not equal to 1, then the Quasi-LR test can still be used to test competing nested models.
see end of section 7.5.1 in Cameron/Trivedi Microeconometrics, which reference
Wooldridge, J. M. (2002), Econometric Analysis of Cross Section and Panel Data, p 370
for general QMLE the LR statistic is weighted sum of chi-squares distributed
Cameron Trivedi Microeconometrics section 8,5,3
(I have already written the distribution for weighted sum of chi-squares random variables, the problem is getting the case specific weights, which are eigenvalues of some matrix products)
The text was updated successfully, but these errors were encountered:
If we have misspecification in the form of simple under/overdispersion, like in GLM or Poisson model with scale not equal to 1, then the Quasi-LR test can still be used to test competing nested models.
see end of section 7.5.1 in Cameron/Trivedi Microeconometrics, which reference
Wooldridge, J. M. (2002), Econometric Analysis of Cross Section and Panel Data, p 370
for general QMLE the LR statistic is weighted sum of chi-squares distributed
Cameron Trivedi Microeconometrics section 8,5,3
(I have already written the distribution for weighted sum of chi-squares random variables, the problem is getting the case specific weights, which are eigenvalues of some matrix products)
The text was updated successfully, but these errors were encountered: