Package: pmlr
Title: Penalized Multinomial Logistic Regression
Version: 1.0
Date: 2010-03-28
Author: Sarah Colby <colby@lunenfeld.ca>, Sophia Lee, Juan Pablo
        Lewinger, Shelley Bull <bull@lunenfeld.ca>
Maintainer: Sarah Colby <colby@lunenfeld.ca>
Description: Extends the approach proposed by Firth (1993) for bias
        reduction of MLEs in exponential family models to the
        multinomial logistic regression model with general covariate
        types.  Modification of the logistic regression score function
        to remove first-order bias is equivalent to penalizing the
        likelihood by the Jeffreys prior, and yields penalized maximum
        likelihood estimates (PLEs) that always exist.  Hypothesis
        testing is conducted via likelihood ratio statistics.  Profile
        confidence intervals (CI) are constructed for the PLEs.
License: GPL (>= 2)
Packaged: 2010-03-29 02:29:55 UTC; Dao & Sarah
Repository: CRAN
Date/Publication: 2010-04-02 17:08:39
Built: R 3.2.5; ; 2016-11-02 14:08:43 UTC; windows
