Fitting and comparing probability distributions with log linear models

DOI10.1016/0167-9473(92)90112-SzbMath0925.62322MaRDI QIDQ1330507

G. Mersch, James K. Lindsey

Publication date: 8 November 1999

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

zbMATH Keywords

probability distributionsgeneralized linear modelslikelihood inferenceloglinear modelsgoodness of fittruncated distributionscomparison of models

Mathematics Subject Classification ID

Generalized linear models (logistic models) (62J12) Linear inference, regression (62J99)

Related Items (3)

Using specially designed exponential families for density estimation ⋮ Stopping rules and the likelihood function ⋮ A Conway-Maxwell-multinomial distribution for flexible modeling of clustered categorical data

Cites Work

• The analysis of categorical data using GLIM
• The Delta Algorithm and GLIM
• Equivalence of Smoothing Parameter Selectors in Density and Intensity Estimation
• The Fitting of Exponential, Weibull and Extreme Value Distributions to Complex Censored Survival Data Using GLIM
• THE TIME INTERVALS BETWEEN INDUSTRIAL ACCIDENTS
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Fitting and comparing probability distributions with log linear models