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

DOI10.1081/STA-200038869zbMath1087.62021MaRDI QIDQ5290395

Anthony G. Pakes

Publication date: 28 April 2006

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

zbMATH Keywords

random contractioncharacterization of probability lawsrandom dilationlength-biasimage invariancemoment sequences and functionsstationary-excess operators

Mathematics Subject Classification ID

Probability distributions: general theory (60E05) Characterization and structure theory of statistical distributions (62E10)

Related Items (1)

ON A GENERALIZATION OF THE STATIONARY EXCESS OPERATOR

Cites Work

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• Characterization by invariance under length-biasing and random scaling
• Characterizations using weighted distributions
• Characterization of laws by balancing weighting against a binary operation
• Characterizations, length-biasing, and infinite divisibility
• Length biasing and laws equivalent to the log-normal
• The renewal-process stationary-excess operator
• LENGTH-BIASING, CHARACTERIZATIONS OF LAWS AND THE MOMENT PROBLEM
• Criteria for the Unique Determination of Probability Distributions by Moments
• On a Certain Class of Limit Distributions

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