Model selection and balanced complexity: AIC, BIC, DIC and beyond

Abstract

Some notes on statistical model selection and comparison, balanced model complexity and predictive accuracy. An overview of different information criteria (AIC, BIC, DIC, WAIC) and cross validation. Mostly taken from Gelman et al.’s recent paper: http://www.stat.columbia.edu/~gelman/research/unpublished/waic_understand.pdf.

Date
5 September 2013
Francisco Rodríguez-Sánchez
Francisco Rodríguez-Sánchez
Researcher

Computational Ecologist & Data Scientist.

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