An accelerated EM algorithm for mixture models with uncertainty for rating data

DOI10.1007/s00180-020-01004-zzbMath1505.62380OpenAlexW3036366057MaRDI QIDQ1995870

Rosaria Simone

Publication date: 25 February 2021

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00180-020-01004-z

zbMATH Keywords

standard errorsrating dataaccelerated EM algorithmcombination of uniform and binomial (CUB)CUB mixture modelsLouis' identity

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Point estimation (62F10)

Related Items (3)

Mixture of shifted binomial distributions for rating data ⋮ Dynamic modelling of price expectations and judgments ⋮ On finite mixtures of discretized beta model for ordered responses

Uses Software

• CUB
• catdata
• FastCUB
• cubremot

Cites Work

• On the identifiability of a mixture model for ordinal data
• Preliminary estimators for a mixture model of ordinal data
• Corrigendum to ``The unimodal model for the classification of ordinal data
• A mixture model for preferences data analysis
• Modeling rating data with nonlinear CUB models
• The class of \textsc{cub} models: statistical foundations, inferential issues and empirical evidence
• Rejoinder to the discussion of ``The class of CUB models: statistical foundations, inferential issues and empirical evidence
• Robust inference for ordinal response models
• Varying uncertainty in CUB models
• Regression for Categorical Data
• Variable Selection in Finite Mixture of Regression Models
• On the Inverse of the Sum of Matrices
• An iterative method for solution of the likelihood equations for incomplete data from exponential families
• Direct Calculation of the Information Matrix via the EM Algorithm
• Model Selection: An Integral Part of Inference
• Model Selection and Multimodel Inference
• A class of mixture models for multidimensional ordinal data
• Cumulative and CUB Models for Rating Data: A Comparative Analysis
• Modelling uncertainty and response styles in ordinal data
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