A model selection criterion for discriminant analysis of high-dimensional data with fewer observations

DOI10.1016/j.jspi.2012.06.002zbMath1348.62204OpenAlexW2060436248MaRDI QIDQ451193

Takayuki Yamada, Masashi Hyodo, Muni S. Srivastava

Publication date: 21 September 2012

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2012.06.002

zbMATH Keywords

discriminant analysisAkaike information criterionhigh-dimensional dataridge-type estimator

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Cites Work

• Estimation of the precision matrix of a singular Wishart distribution and its application in high-dimensional data
• High-dimensional classification using features annealed independence rules
• Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data
• Multivariate Theory for Analyzing High Dimensional Data
• Comparison of Discrimination Methods for High Dimensional Data
• TESTS OF SIGNIFICANCE IN MULTIVARIATE ANALYSIS
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