Clustering in the Presence of Scatter

DOI10.1111/j.1541-0420.2008.01064.xzbMath1168.62061OpenAlexW2000711006WikidataQ51876228 ScholiaQ51876228MaRDI QIDQ3636975

Ranjan Maitra, Ivan P. Ramler

Publication date: 30 June 2009

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://lib.dr.iastate.edu/stat_las_pubs/83

zbMATH Keywords

methylmercuryMCLUSTtight clustering\(k\)-clipsBayes' information criterionbiweight estimatorexact-\(c\)-separation

Mathematics Subject Classification ID

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

Related Items (6)

Unnamed Item ⋮ A Bayesian mixture model to quantify parameters of spatial clustering ⋮ Solution path clustering with adaptive concave penalty ⋮ Robust Clustering Method in the Presence of Scattered Observations ⋮ An efficient k‐means‐type algorithm for clustering datasets with incomplete records ⋮ Batch Effects Correction with Unknown Subtypes

Uses Software

• mclust

Cites Work

• Unnamed Item
• Unnamed Item
• Estimating the Number of Clusters in a Data Set Via the Gap Statistic
• Statistical theory in clustering
• Detecting Features in Spatial Point Processes with Clutter via Model-Based Clustering
• Finding Groups in Data
• Nearest-Neighbor Clutter Removal for Estimating Features in Spatial Point Processes
• How Many Clusters? Which Clustering Method? Answers Via Model-Based Cluster Analysis
• Model-Based Gaussian and Non-Gaussian Clustering
• Model-Based Clustering, Discriminant Analysis, and Density Estimation
• Finite mixture models
• Tight Clustering: A Resampling‐Based Approach for Identifying Stable and Tight Patterns in Data

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