On maximum likelihood estimation for count data models

DOI10.1016/0167-6687(90)90014-5zbMath0724.62103OpenAlexW1965369438MaRDI QIDQ758075

Werner Hürlimann

Publication date: 1990

Published in: Insurance Mathematics \& Economics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-6687(90)90014-5

zbMATH Keywords

infinite divisibilityhyper-Poissondiscrete distributionNecessary and sufficient conditionsclaim frequency modelscontagious count data modelslog-zero Poissonmaximum likelihood equationsmoment estimator equationpseudo-compound Poisson representation

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Point estimation (62F10)

Related Items (9)

On parameter orthogonality to the mean ⋮ The concepts of pseudo compound Poisson and partition representations in discrete probability ⋮ A characterization of the compound multiparameter Hermite gamma distribution via Gauss's principle ⋮ On modeling claim frequency data in general insurance with extra zeros ⋮ On mean scaled insurance risk models ⋮ Robust confidence bounds for the mean of some count data models ⋮ Bivariate Hofmann distributions ⋮ On quasi-infinitely divisible distributions ⋮ Notes on discrete compound Poisson model with applications to risk theory

Cites Work

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• Asymptotic properties of maximum likelihood estimates in the mixed Poisson model
• An elementary proof of the Adelson-Panjer recursion formula
• Recursive formulas for discrete distributions
• Numerical evaluation of the compound Poisson distribution: Recursion or Fast Fourier Transform?
• On the probabilities of the log-zero-poisson distribution
• On species frequency models
• A Two-Parameter Family of Hyper-Poisson Distributions
• Infinite Divisibility of Integer-Valued Random Variables

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