Bootstrapping in a high dimensional but very low-sample size problem

DOI10.1080/00949650902798129zbMath1195.62126OpenAlexW2097095790MaRDI QIDQ3589980

Jeffrey D. Hart, Juhee Song

Publication date: 17 September 2010

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/1969.1/3853

zbMATH Keywords

cluster analysiskernel density estimationmixture modelbootstrap-based testFDR (false discovery rate)HDLSS (high-dimensional, low-sample size) data

Mathematics Subject Classification ID

Density estimation (62G07) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Nonparametric statistical resampling methods (62G09) Paired and multiple comparisons; multiple testing (62J15)

Cites Work

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