Jackknife Empirical Likelihood Inference for the Absolute Mean Deviation

In statistics it is of interest to find a better interval estimator of the absolute mean deviation. In this thesis, we focus on using the jackknife, the adjusted and the extended jackknife empirical likelihood methods to construct confidence intervals for the mean absolute deviation of a random vari...

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Main Author: meng, xueping
Format: Others
Published: Digital Archive @ GSU 2013
Subjects:
Online Access:http://digitalarchive.gsu.edu/math_theses/132
http://digitalarchive.gsu.edu/cgi/viewcontent.cgi?article=1135&context=math_theses
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spelling ndltd-GEORGIA-oai-digitalarchive.gsu.edu-math_theses-11352013-08-03T06:13:07Z Jackknife Empirical Likelihood Inference for the Absolute Mean Deviation meng, xueping In statistics it is of interest to find a better interval estimator of the absolute mean deviation. In this thesis, we focus on using the jackknife, the adjusted and the extended jackknife empirical likelihood methods to construct confidence intervals for the mean absolute deviation of a random variable. The empirical log-likelihood ratio statistics is derived whose asymptotic distribution is a standard chi-square distribution. The results of simulation study show the comparison of the average length and coverage probability by using jackknife empirical likelihood methods and normal approximation method. The proposed adjusted and extended jackknife empirical likelihood methods perform better than other methods for symmetric and skewed distributions. We use real data sets to illustrate the proposed jackknife empirical likelihood methods. 2013-07-15T07:00:00Z text application/pdf http://digitalarchive.gsu.edu/math_theses/132 http://digitalarchive.gsu.edu/cgi/viewcontent.cgi?article=1135&context=math_theses Mathematics Theses Digital Archive @ GSU Confidence interval Coverage probability Jackknife empirical likelihood
collection NDLTD
format Others
sources NDLTD
topic Confidence interval
Coverage probability
Jackknife empirical likelihood
spellingShingle Confidence interval
Coverage probability
Jackknife empirical likelihood
meng, xueping
Jackknife Empirical Likelihood Inference for the Absolute Mean Deviation
description In statistics it is of interest to find a better interval estimator of the absolute mean deviation. In this thesis, we focus on using the jackknife, the adjusted and the extended jackknife empirical likelihood methods to construct confidence intervals for the mean absolute deviation of a random variable. The empirical log-likelihood ratio statistics is derived whose asymptotic distribution is a standard chi-square distribution. The results of simulation study show the comparison of the average length and coverage probability by using jackknife empirical likelihood methods and normal approximation method. The proposed adjusted and extended jackknife empirical likelihood methods perform better than other methods for symmetric and skewed distributions. We use real data sets to illustrate the proposed jackknife empirical likelihood methods.
author meng, xueping
author_facet meng, xueping
author_sort meng, xueping
title Jackknife Empirical Likelihood Inference for the Absolute Mean Deviation
title_short Jackknife Empirical Likelihood Inference for the Absolute Mean Deviation
title_full Jackknife Empirical Likelihood Inference for the Absolute Mean Deviation
title_fullStr Jackknife Empirical Likelihood Inference for the Absolute Mean Deviation
title_full_unstemmed Jackknife Empirical Likelihood Inference for the Absolute Mean Deviation
title_sort jackknife empirical likelihood inference for the absolute mean deviation
publisher Digital Archive @ GSU
publishDate 2013
url http://digitalarchive.gsu.edu/math_theses/132
http://digitalarchive.gsu.edu/cgi/viewcontent.cgi?article=1135&context=math_theses
work_keys_str_mv AT mengxueping jackknifeempiricallikelihoodinferencefortheabsolutemeandeviation
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