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Bibframe Work

Title
Model-based clustering, classification, and density estimation using mclust in R
Type
Text
Monograph
Multimedia
Contribution
Scrucca, Luca (Author)
Fraley, Chris (Author)
Murphy, T. Brendan, 1972- (Author)
Raftery, Adrian E. (Author)
Subject
Cluster analysis--Data processing (LCSH)
Gaussian distribution--Data processing (LCSH)
Estimation theory--Data processing (LCSH)
R (Computer program language) (LCSH)
Language
English
Classification
LCC: QA278.55 (Assigner: dlc) (Status: used by assigner)
DDC: 519.5/302855133 full (Assigner: dlc)(Source: 23/eng20230328)
Supplementary Content
bibliography
index
Content
text
Summary
"Model-based clustering and classification methods provide a systematic statistical approach to clustering, classification, and density estimation via mixture modeling. The model-based framework allows the problems of choosing or developing methods to be understood within the context of statistical modeling"-- Provided by publisher.
Table Of Contents
Finite mixture models
Model-based clustering
Mixture-based classification
Model-based density estimation
Visualizing Gaussian mixture models
Miscellanea.
Authorized Access Point
Scrucca, Luca Model-based clustering, classification, and density estimation using mclust in R
Admin Metadata
Generation Process: DLC marc2bibframe2 v2.5.0
Status: changed
Encoding Level: full
Identified By: bf:Local, 23038335
Change Date: 2023-11-20T13:32:23
Creation Date: 2023-01-14
Description Language: English
Description Modifier: United States, Library of Congress
Description Authentication: Program for Cooperative Cataloging
Assigner: United States, Library of Congress