Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1147994 | Journal of Statistical Planning and Inference | 2009 | 12 Pages |
Abstract
This work introduces specific tools based on phi-divergences to select and check generalized linear models with binary data. A backward selection criterion that helps to reduce the number of explanatory variables is considered. Diagnostic methods based on divergence measures such as a new measure to detect leverage points and two indicators to detect influential points are introduced. As an illustration, the diagnostics are applied to human psychology data.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
J.A. Pardo, M.C. Pardo,