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

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posted on 05.09.2013, 21:32 by Francisco Rodriguez-Sanchez

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 Mostly taken from Gelman et al.'s recent paper: http://www.stat.columbia.edu/~gelman/research/unpublished/waic_understand.pdf.

Slides made directly from R using slidify (slidify.org). Source code available at https://github.com/Pakillo/model_selection.

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