Model Selection in Regression: Application to Tumours in Childhood

Volume 1 - Issue 1

Annah Managa*

Received: August 23, 2018;   Published: September 10, 2018

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Summary

We give a chronological review of the major model selection methods that have been proposed from circa 1960. These model selection procedures include Residual mean square error (MSE), coefficient of multiple determination (R² ), adjusted coefficient of multiple determination (Adj R² ), Estimate of Error Variance (S² ), Stepwise methods, Mallow’s C_p , Akaike information criterion (AIC), Schwarz criterion (BIC). Some of these methods are applied to a problem of developing a model for predicting tumors in childhood using log-linear models. The theoretical review will discuss the problem of model selection in a general setting. The application will be applied to log-linear models in particular.

Keywords: MSE; R² ; Adj R² ; (S² ); Stepwise methods; C_p ; AIC; BIC

Abstract| Introduction| Literature Review| Frequentist Model Selection Criteria| Methods | Results| Discussion| Conclusion And Recommendations| References|