Penalized multimodal mixture logit model
type: Item
instance of: scholarly article
title: Penalized multimodal mixture logit model
zbMATH Open document ID: 1223.62098
author: Shaheena Bashir
author: Edward M. Carter
published in: Computational Statistics
publication date: 2011-02-22T00:00:00Z
review text: A classification problem is considered where the observed classes are mixtures of some subclasses. The multinomial logit model is used to model the dependence between subclasses labels and predictors. A version of the EM algorithm is proposed for fitting the resulting mixture model. This algorithm maximizes a penalized log-likelihood, helping to avoid the overfitting problem. Results of simulations and applications to medical data are presented.
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 62J12
Mathematics Subject Classification ID: 62-08
zbMATH DE Number: 5855614
zbMATH Keywords: EM algorithm
zbMATH Keywords: penalized maximum likelihood estimation
zbMATH Keywords: classification
describes a project that uses: UCI-ml
MaRDI profile type: Publication
full work available at URL: s00180-009-0165-9
OpenAlex ID: W2110615995
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DOI: 10.1007/S00180-009-0165-9
description: scientific article; zbMATH DE number 5855614