Confidence interval estimation of the location and scale parameters of the logistic distribution using pivotal method

H. A. Muttlak; W. A. Abu-Dayyeh; E. Al-Sawi; M. Al-Momani

doi:10.1080/00949650903379572

Confidence interval estimation of the location and scale parameters of the logistic distribution using pivotal method

H. A. Muttlak
, W. A. Abu-Dayyeh
, E. Al-Sawi
, M. Al-Momani

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

Different confidence intervals (CI) will be constructed for the location and scale parameters of the logistic distribution by assuming that one of them is known. The maximum likelihood estimator and several different pivots will be used to construct different CI for the logistic parameters, using simple random sampling (SRS) and ranked set sampling (RSS). They will be compared via their expected lengths and the standard errors of their lengths using computer simulation. The CIs based on the RSS are found to be more efficient, i.e. having shorter expected lengths and smaller standard errors than their competitors based on the SRS.

Original language	English
Pages (from-to)	391-409
Number of pages	19
Journal	Journal of Statistical Computation and Simulation
Volume	81
Issue number	4
DOIs	https://doi.org/10.1080/00949650903379572
State	Published - Apr 2011

Bibliographical note

Funding Information:
This study was performed at the Department of Hepatology and Infectious Diseases, Medical University of Bialystok, Poland, Zurawia 14 15-540 Bialystok, Poland, and was supported by research grant No 3-56972-L from Medical University of Bialystok, Poland.

Keywords

Efficiency
Expected length
Maximum likelihood estimator
Pivotal method
Ranked set sampling
Simple random sampling

ASJC Scopus subject areas

Statistics and Probability
Modeling and Simulation
Statistics, Probability and Uncertainty
Applied Mathematics

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10.1080/00949650903379572

Cite this

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abstract = "Different confidence intervals (CI) will be constructed for the location and scale parameters of the logistic distribution by assuming that one of them is known. The maximum likelihood estimator and several different pivots will be used to construct different CI for the logistic parameters, using simple random sampling (SRS) and ranked set sampling (RSS). They will be compared via their expected lengths and the standard errors of their lengths using computer simulation. The CIs based on the RSS are found to be more efficient, i.e. having shorter expected lengths and smaller standard errors than their competitors based on the SRS.",

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note = "Funding Information: This study was performed at the Department of Hepatology and Infectious Diseases, Medical University of Bialystok, Poland, Zurawia 14 15-540 Bialystok, Poland, and was supported by research grant No 3-56972-L from Medical University of Bialystok, Poland.",

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AU - Al-Momani, M.

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AB - Different confidence intervals (CI) will be constructed for the location and scale parameters of the logistic distribution by assuming that one of them is known. The maximum likelihood estimator and several different pivots will be used to construct different CI for the logistic parameters, using simple random sampling (SRS) and ranked set sampling (RSS). They will be compared via their expected lengths and the standard errors of their lengths using computer simulation. The CIs based on the RSS are found to be more efficient, i.e. having shorter expected lengths and smaller standard errors than their competitors based on the SRS.

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KW - Ranked set sampling

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Confidence interval estimation of the location and scale parameters of the logistic distribution using pivotal method

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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