Minimax estimation for mixtures of wishart distributions

L. R. Haff, P. T. Kim, J. Y. Koo, D. St. P. Richards

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

The space of positive definite symmetric matrices has been studied extensively as a means of understanding dependence in multivariate data along with the accompanying problems in statistical inference. Many books and papers have been written on this subject, and more recently there has been considerable interest in high-dimensional random matrices with particular emphasis on the distribution of certain eigenvalues. With the availability of modern data acquisition capabilities, smoothing or nonparametric techniques are required that go beyond those applicable only to data arising in Euclidean spaces. Accordingly, we present a Fourier method of minimax Wishart mixture density estimation on the space of positive definite symmetric matrices.

Original languageEnglish (US)
Pages (from-to)3417-3440
Number of pages24
JournalAnnals of Statistics
Volume39
Issue number6
DOIs
StatePublished - Dec 2011

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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