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Open AccessJournal ArticleDOI

Empirical likelihood-based tests for stochastic ordering

Hammou El Barmi, +1 more
- 01 Feb 2013 - 
- Vol. 19, Iss: 1, pp 295-307
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TLDR
In this paper, an empirical likelihood approach to test for the presence of stochastic ordering among univariate distributions based on independent random samples from each distribution is proposed. But the approach is used to compare the lengths of rule of Roman Emperors over various historical periods, including the decline and fall of the empire.
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.

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References
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Book

Convergence of Probability Measures

TL;DR: Weak Convergence in Metric Spaces as discussed by the authors is one of the most common modes of convergence in metric spaces, and it can be seen as a form of weak convergence in metric space.
Journal ArticleDOI

Convergence of Probability Measures

TL;DR: Convergence of Probability Measures as mentioned in this paper is a well-known convergence of probability measures. But it does not consider the relationship between probability measures and the probability distribution of probabilities.
Journal ArticleDOI

Empirical likelihood ratio confidence intervals for a single functional

TL;DR: In this article, the empirical distribution function based on a sample is used to define a likelihood ratio function for distributions, which can be used to construct confidence intervals for the sample mean, for a class of M-estimates that includes quantiles, and for differentiable statistical functionals.
Book

Order restricted statistical inference

TL;DR: In this paper, a set of multinomial parameters are derived about distributions subject to shape restrictions, and a conditional expectation given a sigma-lattice is given in a more general setting.
Journal ArticleDOI

Empirical Likelihood Ratio Confidence Regions

Art B. Owen
- 01 Mar 1990 - 
TL;DR: In this article, an empirical likelihood ratio function is defined and used to obtain confidence regions for vector valued statistical functionals, and an effective method is presented for computing empirical profile likelihoods for the mean of a vector random variable.
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