Asymptotic properties of a double penalized maximum likelihood estimator in logistic regression

Sujuan Gao, Jianzhao Shen

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Maximum likelihood estimates in logistic regression may encounter serious bias or even non-existence with many covariates or with highly correlated covariates. In this paper, we show that a double penalized maximum likelihood estimator is asymptotically consistent in large samples.

Original languageEnglish
Pages (from-to)925-930
Number of pages6
JournalStatistics and Probability Letters
Volume77
Issue number9
DOIs
StatePublished - May 1 2007

Fingerprint

Penalized Maximum Likelihood
Logistic Regression
Maximum Likelihood Estimator
Asymptotic Properties
Covariates
Maximum Likelihood Estimate
Nonexistence
Maximum likelihood estimator
Logistic regression
Asymptotic properties
Maximum likelihood

Keywords

  • Logistic regression
  • Maximum likelihood
  • Penalized maximum likelihood
  • Ridge regression

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Statistics and Probability

Cite this

Asymptotic properties of a double penalized maximum likelihood estimator in logistic regression. / Gao, Sujuan; Shen, Jianzhao.

In: Statistics and Probability Letters, Vol. 77, No. 9, 01.05.2007, p. 925-930.

Research output: Contribution to journalArticle

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