{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

Chapter 2 Notes

Select model with minimum aic unm for our example aic0

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

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 =...
View Full Document

{[ snackBarMessage ]}

Ask a homework question - tutors are online