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Clustering high dimension, low sample size data using the maximal data piling distance

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Publication:5894806
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DOI10.5705/ss.2010.148zbMath1253.62047OpenAlexW2325127698MaRDI QIDQ5894806

Mihye Ahn, Wen-Bin Lu, Hao Helen Zhang

Publication date: 21 December 2012

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: http://www3.stat.sinica.edu.tw/statistica/j22n4/J22N48/J22N48.html


zbMATH Keywords

shrinkage estimationhard thresholdingvariance component selection


Mathematics Subject Classification ID

Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).


Related Items (6)

Adaptive LASSO for linear mixed model selection via profile log-likelihood ⋮ Spike-and-slab type variable selection in the Cox proportional hazards model for high-dimensional features ⋮ Model selection in linear mixed-effect models ⋮ Shrinkage estimation in linear mixed models for longitudinal data ⋮ A simultaneous variable selection methodology for linear mixed models ⋮ Random effects selection in generalized linear mixed models via shrinkage penalty function


Uses Software

  • OSCAR
  • NLPLIB
  • OPERA
  • SeDuMi
  • YALMIP



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