Robust Inference and Modeling of Mean and Dispersion for Generalized Linear Models-Reference-Cited by-同舟云学术

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Robust Inference and Modeling of Mean and Dispersion for Generalized Linear Models

Published:2023-01-11 Issue: Volume: Page:1-12
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

Ponnet Jolien¹^ORCID,Segaert Pieter¹,Van Aelst Stefan¹^ORCID,Verdonck Tim¹²^ORCID

Affiliation:

1. Department of Mathematics, KU Leuven, Leuven, Belgium

2. Department of Mathematics, University of Antwerp, Antwerp, Belgium

Funder

International Funds KU Leuven

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2022.2140054

Reference62 articles.

1. Robust inference in the negative binomial regression model with an application to falls data

2. Saddlepoint tests for accurate and robust inference on overdispersed count data

3. An Outlier-Robust Fit for Generalized Additive Models With Applications to Disease Outbreak Detection

4. A robust conditional maximum likelihood estimator for generalized linear models with a dispersion parameter

5. Joint estimation and variable selection for mean and dispersion in proper dispersion models

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Robust and sparse logistic regression;Advances in Data Analysis and Classification;2023-11-27

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