Analytical closed-form solution for binary logit regression by categorical predictors

DOI10.1080/02664763.2014.932760OpenAlexW2065972402MaRDI QIDQ5130120

Stan Lipovetsky

Publication date: 4 November 2020

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

Full work available at URL: https://doi.org/10.1080/02664763.2014.932760

zbMATH Keywords

likelihood functioncontingency tableclosed-form analytical solutioncategorical predictorsbinary logit model

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Closed-form maximum likelihood estimator for generalized linear models in the case of categorical explanatory variables: application to insurance loss modeling

Cites Work

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• CONDITIONAL AND MULTINOMIAL LOGITS AS BINARY LOGIT REGRESSIONS
• Applied Multivariate Statistical Analysis
• An Algorithm for Exact Logistic Regression
• Modern Multivariate Statistical Techniques
• Ordinal Data Modeling
• Discrete Choice Methods with Simulation
• Double logistic curve in regression modeling

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