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Hi Sir, Thanks for making package available to us. I am facing few problems if you can give some hints: Problem-1: The model summary and residual deviance matched (in the mail below) but I didn't understand why AIC is still different. > AIC(m1) [1] 532965 > AIC(m1big_longer) [1] 101442.9 Problem-2: chunksize argument is there in bigglm but not in biglm, consequently, udate.biglm is there, but not update.bigglm Is my observation correct? If yes, why is this difference? Regards Utkarsh / / From: Thomas Lumley <tlumley_at_u.washington.edu <mailto:tlumley_...

Dear all, I am using the bigglm package to fit a few GLM's to a large dataset (3 million rows, 6 columns). While trying to fit a Poisson GLM I noticed that the coefficient estimates were very different from what I obtained when estimating the model on a smaller dataset using glm(), I wrote a very basic toy example to compare the results of bigglm() against a glm() call. Consider the

...utkarshsinghal wrote: Hi Sir, Thanks for making package available to us. I am facing few problems if you can give some hints: Problem-1: The model summary and residual deviance matched (in the mail below) but I didn't understand why AIC is still different. AIC(m1) [1] 532965 AIC(m1big_longer) [1] 101442.9 That's because AIC.default uses the unnormalized loglikelihood and AIC.biglm uses the deviance.  Only differences in AIC between models are meaningful, not individual values. Problem-2: chunksize argument is there in bigglm but not in biglm, consequently, udate..biglm is t...