Characterization of Probability Laws via Length-Biasing and Stationary-Excess Operations

Anthony Pakes

doi:10.1081/STA-200038869

Characterization of Probability Laws via Length-Biasing and Stationary-Excess Operations

Anthony Pakes

UWA Business School

Research output: Contribution to journal › Article

2 Citations (Scopus)

Abstract

The gamma and uniform laws have been characterized by relating their moment sequences to the moments of the corresponding renewal forward recurrence time laws. Here this work is re-examined in a more general distributional setting, exposing its fundamental relation to length-biasing, and obtaining various generalizations.

Original language	English
Pages (from-to)	2975-2992
Journal	Communications in Statistics - Theory and Methods
Volume	33
Issue number	12
DOIs	https://doi.org/10.1081/STA-200038869
Publication status	Published - 2004

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title = "Characterization of Probability Laws via Length-Biasing and Stationary-Excess Operations",

abstract = "The gamma and uniform laws have been characterized by relating their moment sequences to the moments of the corresponding renewal forward recurrence time laws. Here this work is re-examined in a more general distributional setting, exposing its fundamental relation to length-biasing, and obtaining various generalizations.",

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AB - The gamma and uniform laws have been characterized by relating their moment sequences to the moments of the corresponding renewal forward recurrence time laws. Here this work is re-examined in a more general distributional setting, exposing its fundamental relation to length-biasing, and obtaining various generalizations.

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DO - 10.1081/STA-200038869

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JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

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