Latent class regression model in IRLS approach

DOI10.1016/J.MCM.2005.01.031zbMath1079.62063OpenAlexW2059910125MaRDI QIDQ815330

Stan Lipovetsky, W. Michael Conklin

Publication date: 16 February 2006

Published in: Mathematical and Computer Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.mcm.2005.01.031

zbMATH Keywords

iteratively reweighted least squareslatent classes

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Point estimation (62F10)

Related Items (4)

Finding cluster centers and sizes via multinomial parameterization ⋮ SURF — STRUCTURAL UNDUPLICATED REACH AND FREQUENCY: LATENT CLASS TURF AND SHAPLEY VALUE ANALYSES ⋮ Cluster-based \(L2\) re-weighted regression ⋮ Thurstone scaling in order statistics

Uses Software

• Latent GOLD

Cites Work

• Identifiability of models for clusterwise linear regression
• Thurstone scaling via binary response regression
• A System of Subroutines for Iteratively Reweighted Least Squares Computations
• Analysis of regression in game theory approach
• Dual‐ and triple‐mode matrix approximation and regression modelling
• A latent‐class regression approach for the analysis of recurrent choice data
• A simple and fast alternative to the EM algorithm for incomplete categorical data and latent class models.
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Latent class regression model in IRLS approach