Semiparametric Multinomial Logistic Regression for Multivariate Point Pattern Data

Multinomial logistic regression

Multinomial logistic regression is the extension for the (binary) logistic regression when the categorical dependent outcome has more than two levels. For example, instead of predicting only dead or alive, we may have three groups, namely: dead, lost to follow-up, and alive. In the analysis to follow, a reference group has to be chosen for comparison, the appropriate group would be the alive, i...

Multinomial Logistic Regression Ensembles

This article proposes a method for multiclass classification problems using ensembles of multinomial logistic regression models. A multinomial logit model is used as a base classifier in ensembles from random partitions of predictors. The multinomial logit model can be applied to each mutually exclusive subset of the feature space without variable selection. By combining multiple models the pro...

Logistic Regression for Multivariate Longitudinal Ordinal Data

Multinomial Logistic Regression with SPSS

Subjects were engineering majors recruited from a freshman-level engineering class from 2007 through 2010. Data were obtained for 256 students. The outcome variable of interest was retention group: Those who were still active in our engineering program after two years of study were classified as persisters. Those who were no longer in our engineering program were classified as having left in go...

Bayesian Multinomial Logistic Regression for Author Identification

Motivated by high-dimensional applications in authorship atttribution, we describe a Bayesian multinomial logistic regression model together with an associated learning algorithm.