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Variable Selection for Latent Class Analysis with Application to Low Back Pain Diagnosis
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Variable Selection for Latent Class Analysis with Application to Low Back Pain Diagnosis

Michael Fop
K. Smart
T. B. Murphy
    CML
ArXiv (abs)PDFHTML

Papers citing "Variable Selection for Latent Class Analysis with Application to Low Back Pain Diagnosis"

7 / 7 papers shown
Title
Variable selection for clustering with Gaussian mixture models: state of the art
Variable selection for clustering with Gaussian mixture models: state of the art
Abdelghafour Talibi
B. Achchab
R. Lasri
60
15
0
31 Jan 2017
clustvarsel: A Package Implementing Variable Selection for Model-based Clustering in R
clustvarsel: A Package Implementing Variable Selection for Model-based Clustering in R
Luca Scrucca
A. Raftery
55
75
0
03 Nov 2014
Bayesian variable selection for latent class analysis using a collapsed Gibbs sampler
Bayesian variable selection for latent class analysis using a collapsed Gibbs sampler
Arthur J. White
J. Wyse
T. B. Murphy
71
49
0
27 Feb 2014
Model-based clustering for conditionally correlated categorical data
Model-based clustering for conditionally correlated categorical data
M. Marbac
C. Biernacki
V. Vandewalle
CML
84
35
0
22 Jan 2014
Mixture of Latent Trait Analyzers for Model-Based Clustering of Categorical Data
Mixture of Latent Trait Analyzers for Model-Based Clustering of Categorical Data
Isabella Gollini
T. B. Murphy
65
84
0
10 Jan 2013
Clustering and variable selection for categorical multivariate data
Clustering and variable selection for categorical multivariate data
D. Bontemps
Wilson Toussile
92
15
0
05 Feb 2010
Penalized model-based clustering with cluster-specific diagonal covariance matrices and grouped variables
Penalized model-based clustering with cluster-specific diagonal covariance matrices and grouped variables
Benhuai Xie
Wei Pan
Xiaotong Shen
137
81
0
21 Feb 2008

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