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Perturbation of matrices and nonnegative rank with a view toward statistical models

  • Cristiano Bocci
  • , Enrico Carlini
  • , Fabio Rapallo

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper we study how perturbing a matri x changes its nonnegative rank. We prove that the nonnegative rank can only increase in a neighborhood of a matrix with no zero columns. Also, we describe some special families of perturbations. We show how our results relate to statistics in terms of the study of maximum likelihood estimation for mixture models.

Original languageEnglish
Pages (from-to)1500-1512
Number of pages13
JournalSIAM Journal on Matrix Analysis and Applications
Volume32
Issue number4
DOIs
Publication statusPublished - 2011
Externally publishedYes

Keywords

  • Frobenius norm
  • Independence of random variables
  • Jacobian matrix
  • Mixture models

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