Allometric extension model for conditional distributions

Hiroshi Kurata, Takahiro Hoshino, Yasunori Fujikoshi

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

When two groups are present, they are said to form an allometric model, if one group is the extension of the other group along the main axis of variation. The model is widely used in the context of principal component analysis, especially for the description of growth processes of creatures. In this paper, the notion of allometric extension model is applied to conditional distributions. More specifically, we derive a sufficient condition, for which the two conditional distributions given the sign of the first principal component form an allometric extension model.

Original languageEnglish
Pages (from-to)1985-1998
Number of pages14
JournalJournal of Multivariate Analysis
Volume99
Issue number9
DOIs
Publication statusPublished - 2008 Oct
Externally publishedYes

Fingerprint

Conditional Distribution
Growth Process
Principal Components
Model
Principal component analysis
Principal Component Analysis
Conditional distribution
Sufficient Conditions

Keywords

  • 62E17
  • 62H25
  • Allometric extension
  • Conditional distribution
  • Principal component analysis
  • Scale mixture of normal distributions

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Numerical Analysis
  • Statistics and Probability

Cite this

Allometric extension model for conditional distributions. / Kurata, Hiroshi; Hoshino, Takahiro; Fujikoshi, Yasunori.

In: Journal of Multivariate Analysis, Vol. 99, No. 9, 10.2008, p. 1985-1998.

Research output: Contribution to journalArticle

Kurata, Hiroshi ; Hoshino, Takahiro ; Fujikoshi, Yasunori. / Allometric extension model for conditional distributions. In: Journal of Multivariate Analysis. 2008 ; Vol. 99, No. 9. pp. 1985-1998.
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