Clustering in the Presence of Scatter
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Publication:3636975
DOI10.1111/j.1541-0420.2008.01064.xzbMath1168.62061OpenAlexW2000711006WikidataQ51876228 ScholiaQ51876228MaRDI QIDQ3636975
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
methylmercuryMCLUSTtight clustering\(k\)-clipsBayes' information criterionbiweight estimatorexact-\(c\)-separation
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
Cites Work
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- 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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