Pseudo Likelihood Ratio Confidence Intervals for the Mean of a Population Containing Many Zero Values under Unequal Probability Sampling

碩士 === 淡江大學 === 數學學系碩士班 === 97 === The many-zero-observation data in survey sampling under complex probability sampling is considered. The confidence interval derived using the traditional normal approximation based on the central limit theorem (CLT) has poor coverage rate even when the sample size...

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Main Authors: Yu-Jyuan Su, 蘇育娟
Other Authors: Shun-Yi Chen
Format: Others
Language:zh-TW
Published: 2009
Online Access:http://ndltd.ncl.edu.tw/handle/96633296887057125771
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spelling ndltd-TW-097TKU054790032015-10-13T16:13:30Z http://ndltd.ncl.edu.tw/handle/96633296887057125771 Pseudo Likelihood Ratio Confidence Intervals for the Mean of a Population Containing Many Zero Values under Unequal Probability Sampling 不等機率抽樣下擬概度比方法求多零值資料的信賴區間 Yu-Jyuan Su 蘇育娟 碩士 淡江大學 數學學系碩士班 97 The many-zero-observation data in survey sampling under complex probability sampling is considered. The confidence interval derived using the traditional normal approximation based on the central limit theorem (CLT) has poor coverage rate even when the sample size is large. The maximum likelihood method (ML) of Kvanli et al (1998) does not work well either. This paper expands the pseudo likelihood method of Chen and Sitter (1999) that integrated unequal probability sampling design (Cochran, 1977). The method utilizes auxiliary information which has a correlation coefficient ρ with the data. A comparison between different methods was conducted under distinct ρ values and nonzero proportion α, and various nonzero distributions. Simulation results indicate that the pseudo likelihood method improves the coverage rate substantially and outperforms the CLT and ML methods. Shun-Yi Chen 陳順益 2009 學位論文 ; thesis 93 zh-TW
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language zh-TW
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description 碩士 === 淡江大學 === 數學學系碩士班 === 97 === The many-zero-observation data in survey sampling under complex probability sampling is considered. The confidence interval derived using the traditional normal approximation based on the central limit theorem (CLT) has poor coverage rate even when the sample size is large. The maximum likelihood method (ML) of Kvanli et al (1998) does not work well either. This paper expands the pseudo likelihood method of Chen and Sitter (1999) that integrated unequal probability sampling design (Cochran, 1977). The method utilizes auxiliary information which has a correlation coefficient ρ with the data. A comparison between different methods was conducted under distinct ρ values and nonzero proportion α, and various nonzero distributions. Simulation results indicate that the pseudo likelihood method improves the coverage rate substantially and outperforms the CLT and ML methods.
author2 Shun-Yi Chen
author_facet Shun-Yi Chen
Yu-Jyuan Su
蘇育娟
author Yu-Jyuan Su
蘇育娟
spellingShingle Yu-Jyuan Su
蘇育娟
Pseudo Likelihood Ratio Confidence Intervals for the Mean of a Population Containing Many Zero Values under Unequal Probability Sampling
author_sort Yu-Jyuan Su
title Pseudo Likelihood Ratio Confidence Intervals for the Mean of a Population Containing Many Zero Values under Unequal Probability Sampling
title_short Pseudo Likelihood Ratio Confidence Intervals for the Mean of a Population Containing Many Zero Values under Unequal Probability Sampling
title_full Pseudo Likelihood Ratio Confidence Intervals for the Mean of a Population Containing Many Zero Values under Unequal Probability Sampling
title_fullStr Pseudo Likelihood Ratio Confidence Intervals for the Mean of a Population Containing Many Zero Values under Unequal Probability Sampling
title_full_unstemmed Pseudo Likelihood Ratio Confidence Intervals for the Mean of a Population Containing Many Zero Values under Unequal Probability Sampling
title_sort pseudo likelihood ratio confidence intervals for the mean of a population containing many zero values under unequal probability sampling
publishDate 2009
url http://ndltd.ncl.edu.tw/handle/96633296887057125771
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