Identifiability of Mixtures

G. M. Tallis; P. Chesson

doi:10.1017/S1446788700024897

Identifiability of Mixtures

G. M. Tallis, P. Chesson

Ecology and Evolutionary Biology

Research output: Contribution to journal › Article › peer-review

19 Scopus citations

Abstract

Let F(x, 0) be a family of distribution functions indexed by If G(0) is a distribution function on 12, H(x) = f_QF(x, 0) dG(B) is a mixture with respect to G. If there is a unique G yielding H, the mixture is said to be identifiable. This paper summarises some known results related to identifiability of special types of mixtures and then discusses the general problem of identifiability in terms of mappings. Some new results follow for mappings with special features.

Original language	English (US)
Pages (from-to)	339-348
Number of pages	10
Journal	Journal of the Australian Mathematical Society
Volume	32
Issue number	3
DOIs	https://doi.org/10.1017/S1446788700024897
State	Published - 1982

Keywords

bounded inverse
identifiability
kernel
linear independence
mixture
strong independence
unbounded inverse

ASJC Scopus subject areas

General Mathematics

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10.1017/S1446788700024897

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abstract = "Let F(x, 0) be a family of distribution functions indexed by If G(0) is a distribution function on 12, H(x) = fQF(x, 0) dG(B) is a mixture with respect to G. If there is a unique G yielding H, the mixture is said to be identifiable. This paper summarises some known results related to identifiability of special types of mixtures and then discusses the general problem of identifiability in terms of mappings. Some new results follow for mappings with special features.",

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AB - Let F(x, 0) be a family of distribution functions indexed by If G(0) is a distribution function on 12, H(x) = fQF(x, 0) dG(B) is a mixture with respect to G. If there is a unique G yielding H, the mixture is said to be identifiable. This paper summarises some known results related to identifiability of special types of mixtures and then discusses the general problem of identifiability in terms of mappings. Some new results follow for mappings with special features.

KW - bounded inverse

KW - identifiability

KW - kernel

KW - linear independence

KW - mixture

KW - strong independence

KW - unbounded inverse

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Identifiability of Mixtures

Abstract

Keywords

ASJC Scopus subject areas

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