Penalized robust estimators in sparse logistic regression-Reference-Cited by-同舟云学术

Penalized robust estimators in sparse logistic regression

Published:2021-11-12 Issue: Volume: Page:
ISSN:1133-0686
Container-title:TEST
language:en
Short-container-title:TEST

Author:

Bianco Ana M.,Boente Graciela,Chebi Gonzalo

Funder

Secretaria de Ciencia y Tecnica, Universidad de Buenos Aires

Fondo para la Investigación Científica y Tecnológica

Ministerio de Economía, Industria y Competitividad, Gobierno de España

Publisher

Springer Science and Business Media LLC

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://link.springer.com/content/pdf/10.1007/s11749-021-00792-w.pdf

Reference34 articles.

1. Avella-Medina M, Ronchetti E (2018) Robust and consistent variable selection in high-dimensional generalized linear models. Biometrika 105:31–44

2. Basu A, Gosh A, Mandal A, Martin N, Pardo L (2017) A Wald-type test statistic for testing linear hypothesis in logistic regression models based on minimum density power divergence estimator. Electr J Stat 11:2741–2772

3. Bianco A, Martínez E (2009) Robust testing in the logistic regression model. Comput Stat Data Anal 53:4095–4105

4. Bianco A, Yohai V (1996) Robust estimation in the logistic regression model. Lecture Notes Stat 109:17–34

5. Bondell HD (2005) Minimum distance estimation for the logistic regression model. Biometrika 92:724–731

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