BOOTSTRAP CALIBRATION AND EMPIRICAL LIKELIHOOD IN THE LOGISTIC REGRESSION MODEL(Categorical Data Analysis)

Abstract

In this paper we introduce a bootstrap approximation for the sampling distribution of the empirical likelihood ratio statistic in the logistic regression model. Both classical and robust inference procedures are considered. Some results of a Monte Carlo experiment illustrate the effectiveness of the proposed approach.

Journal

Journal of the Japanese Society of Computational Statistics   [List of Volumes]

Journal of the Japanese Society of Computational Statistics 15(2), 247-254, 2003-06  [Table of Contents]

Japanese Society of Computational Statistics

References:  14

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Codes

  • NII Article ID (NAID) :
    110001235178
  • NII NACSIS-CAT ID (NCID) :
    AA10823693
  • Text Lang :
    ENG
  • Article Type :
    REV
  • ISSN :
    09152350
  • Databases :
    CJP  NII-ELS 

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