Invariance theorems for Fisher information

Murray D. Smith

doi:10.1080/03610920701215159

Invariance theorems for Fisher information

Murray D. Smith^*

^*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

In multivariate and multi-parameter contexts, new expressions for Fisher Information are derived using the copula representation of the joint distribution of random variables. Invariance of Fisher Information to margins of the joint distribution is then demonstrated.

Original language	English
Pages (from-to)	2213-2222
Number of pages	10
Journal	Communications in Statistics - Theory and Methods
Volume	36
Issue number	12
DOIs	https://doi.org/10.1080/03610920701215159
Publication status	Published - 28 Aug 2007
Externally published	Yes

Keywords

Copula
Copula representation
Dependence parameter
Fisher Information
Invariance
Margin parameter

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10.1080/03610920701215159

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title = "Invariance theorems for Fisher information",

abstract = "In multivariate and multi-parameter contexts, new expressions for Fisher Information are derived using the copula representation of the joint distribution of random variables. Invariance of Fisher Information to margins of the joint distribution is then demonstrated.",

keywords = "Copula, Copula representation, Dependence parameter, Fisher Information, Invariance, Margin parameter",

author = "Smith, \{Murray D.\}",

year = "2007",

month = aug,

day = "28",

doi = "10.1080/03610920701215159",

language = "English",

volume = "36",

pages = "2213--2222",

journal = "Communications in Statistics - Theory and Methods",

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T1 - Invariance theorems for Fisher information

AU - Smith, Murray D.

PY - 2007/8/28

Y1 - 2007/8/28

N2 - In multivariate and multi-parameter contexts, new expressions for Fisher Information are derived using the copula representation of the joint distribution of random variables. Invariance of Fisher Information to margins of the joint distribution is then demonstrated.

AB - In multivariate and multi-parameter contexts, new expressions for Fisher Information are derived using the copula representation of the joint distribution of random variables. Invariance of Fisher Information to margins of the joint distribution is then demonstrated.

KW - Copula

KW - Copula representation

KW - Dependence parameter

KW - Fisher Information

KW - Invariance

KW - Margin parameter

UR - https://www.scopus.com/pages/publications/34548349033

U2 - 10.1080/03610920701215159

DO - 10.1080/03610920701215159

M3 - Article

AN - SCOPUS:34548349033

SN - 0361-0926

VL - 36

SP - 2213

EP - 2222

JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

IS - 12

ER -

Invariance theorems for Fisher information

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Keywords

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