A semi-analytical solution to the maximum-likelihood fit of Poisson data to a linear model using the Cash statistic

DOI10.1080/02664763.2020.1820960OpenAlexW3088487581MaRDI QIDQ5085628

David Spence, Massimiliano Bonamente

Publication date: 27 June 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2009.07915

zbMATH Keywords

parameter estimationprobabilitystatisticsmaximum-likelihood methodsCash statistic

Mathematics Subject Classification ID

Point estimation (62F10) Parametric inference under constraints (62F30) Applications of statistics (62Pxx)

Uses Software

• dobson

Cites Work

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• A flexible regression model for count data
• Vector generalized linear and additive models. With an implementation in R
• Statistics and Analysis of Scientific Data
• A novel Bayesian regression model for counts with an application to health data
• Probability models of chance fluctuations in spectra of astronomical sources with applications to X-ray absorption lines
• Extended Poisson–Tweedie: Properties and regression models for count data
• An Introduction to Generalized Linear Models, Fourth Edition
• A Useful Distribution for Fitting Discrete Data: Revival of the Conway–Maxwell–Poisson Distribution
• Distribution of the C statistic with applications to the sample mean of Poisson data

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