Clustering data with measurement errors

DOI10.1016/j.csda.2006.12.012zbMath1445.62151OpenAlexW2125319195MaRDI QIDQ1020711

Nitin R. Patel, Mahesh Kumar

Publication date: 2 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2006.12.012

zbMATH Keywords

model-based clusteringmaximum likelihoodincome dataMarkov chains clusteringtime-series clustering

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Linear regression; mixed models (62J05) Markov processes: estimation; hidden Markov models (62M05)

Related Items (4)

An optimized k-harmonic means algorithm combined with modified particle swarm optimization and Cuckoo Search algorithm ⋮ Gaussian mixture modeling and model-based clustering under measurement inconsistency ⋮ QuantifyingR²bias in the presence of measurement error ⋮ Using clustering to improve sales forecasts in retail merchandising

Cites Work

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• Clusters of time series
• A DISTANCE MEASURE FOR CLASSIFYING ARIMA MODELS
• On Grouping for Maximum Homogeneity
• An approach of clustering data with noisy or imprecise feature measurement
• Model-Based Gaussian and Non-Gaussian Clustering
• Model-Based Clustering, Discriminant Analysis, and Density Estimation

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