Chapter 2 Notes

Select model with minimum aic unm for our example aic0

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Unformatted text preview: Akaike Information Criterion AIC. ˆ AIC = −2l (θ; Y ) + 2p where p is the number of parameters in the statistical model. Select model with minimum AIC . UNM For our example, AIC0 = 2(68.3868) + 2(1) = 138.7736 AIC1 = 2(67.0230) + 2(2) = 138.046 So the preferred model is θ1 = θ2 but barely. AIC rewards goodness of fit or models with large likelihood Includes penalty that increases with number of parameters. Attempts to avoid overfitting. Different penalties provide different criteria, ˆ BIC =...
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This note was uploaded on 01/27/2014 for the course STAT 574 taught by Professor Gabrielhuerta during the Fall '13 term at New Mexico.

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