Literature DB >> 23874142

Empirical likelihood-based tests for stochastic ordering.

Hammou El Barmi1, Ian W McKeague.   

Abstract

This paper develops an empirical likelihood approach to testing for the presence of stochastic ordering among univariate distributions based on independent random samples from each distribution. The proposed test statistic is formed by integrating a localized empirical likelihood statistic with respect to the empirical distribution of the pooled sample. The asymptotic null distribution of this test statistic is found to have a simple distribution-free representation in terms of standard Brownian bridge processes. The approach is used to compare the lengths of rule of Roman Emperors over various historical periods, including the "decline and fall" phase of the empire. In a simulation study, the power of the proposed test is found to improve substantially upon that of a competing test due to El Barmi and Mukerjee.

Entities:  

Keywords:  distribution-free; nonparametric likelihood ratio testing; order restricted inference

Year:  2013        PMID: 23874142      PMCID: PMC3716296          DOI: 10.3150/11-BEJ393SUPP

Source DB:  PubMed          Journal:  Bernoulli (Andover)        ISSN: 1350-7265            Impact factor:   1.595


  4 in total

1.  Tests for stochastic ordering under biased sampling.

Authors:  Hsin-Wen Chang; Hammou El Barmi; Ian W McKeague
Journal:  J Nonparametr Stat       Date:  2016-10-05       Impact factor: 1.231

2.  Empirical likelihood based tests for stochastic ordering under right censorship.

Authors:  Hsin-Wen Chang; Ian W McKeague
Journal:  Electron J Stat       Date:  2016-09-08       Impact factor: 1.125

3.  COMBINING ISOTONIC REGRESSION AND EM ALGORITHM TO PREDICT GENETIC RISK UNDER MONOTONICITY CONSTRAINT.

Authors:  Jing Qin; Tanya P Garcia; Yanyuan Ma; Ming-Xin Tang; Karen Marder; Yuanjia Wang
Journal:  Ann Appl Stat       Date:  2014       Impact factor: 2.083

4.  Extensions of empirical likelihood and chi-squared-based tests for ordered alternatives.

Authors:  M Carmen Pardo; Ying Lu; Alba M Franco-Pereira
Journal:  J Appl Stat       Date:  2020-07-23       Impact factor: 1.416

  4 in total

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