Variable Selection for Skewed Model-Based Clustering: Application to the Identification of Novel Sleep Phenotypes

DOI10.1080/01621459.2017.1330202zbMath1398.62347OpenAlexW2640502922WikidataQ64939884 ScholiaQ64939884MaRDI QIDQ4690931

Satish Iyengar, Daniel J. Buysse, Martica Hall, Anne Germain, Meredith L. Wallace

Publication date: 23 October 2018

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc6510512

zbMATH Keywords

mixture modelskewed datainsomniaresearch domain criteria

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Statistical ranking and selection procedures (62F07)

Related Items (4)

An evolutionary algorithm with crossover and mutation for model-based clustering ⋮ Variable selection methods for model-based clustering ⋮ An overview on the progeny of the skew-normal family -- a personal perspective ⋮ Mixture of hidden Markov models for accelerometer data

Uses Software

• mclust
• R
• clustvarsel
• PGMM
• mixture
• EMMIXcskew
• Emmixuskew
• sparcl

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