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Return AIC, AICc or BIC from a glm object. Description. For glm fits the family's aic () function is used to compute the AIC. The choice between different criteria is

View source: R/bictab.R. Description. This function creates a model selection table based on the Bayesian information criterion (Schwarz 1978, Burnham and Anderson 2002). The table ranks the models based on the BIC and also provides delta BIC and BIC model weights.

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Only k = 2 gives the genuine AIC; k = log (n) is sometimes referred to as BIC or SBC. Highly active question.

Note that, these regression metrics are all internal measures, that is they have been computed on the same data that was used to build the regression model. Teams.
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2019-07-17 · The fact that R runs on in-memory data is the biggest issue that you face when trying to use Big Data in R. The data has to fit into the RAM on your machine, and it’s not even 1:1. Because you’re actually doing something with the data, a good rule of thumb is that your machine needs 2-3x the RAM of the size of your data.

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From this perspective, the only thing that matters is that R is consistent when computing the AIC and BIC across models of the same type (e.g., binomial logistic regression models). Just to clarify: g_bern is a binary logistic regression model, whereas g_binom is a binomial logistic regression model.

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