Strimenopoulou, F. and Brown, P.J. (2008) Empirical Bayes logistic regression. Statistical Applications in Genetics and Molecular Biology, 7 (2). ISSN 1544-6115 .
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We construct a diagnostic predictor for patient disease status based on a single data set of mass spectra of serum samples together with the binary case-control response. The model is logistic regression with Bernoulli log-likelihood augmented either by quadratic ridge or absolute $L_1$ penalties. For ridge penalization using the singular value decomposition we reduce the the number of variables for maximization to the rank of the design matrix. With log-likelihood loss, 10-fold cross-validatory choice is employed to specify the penalization hyperparameter. Predictive ability is judged on a set-aside subset of the data.
|Additional information:||Article No 9|
|Subjects:||Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics|
|Divisions:||Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics|
|Depositing User:||Philip J Brown|
|Date Deposited:||07 Mar 2009 13:00|
|Last Modified:||14 Jan 2010 14:30|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/8191 (The current URI for this page, for reference purposes)|
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