Estimation of the Mean of the Exponential Distribution Using Maximum Ranked Set Sampling with Unequal Samples | Zendy

B. S. Biradar | Zendy; C. D. Santosha | Zendy

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Estimation of the Mean of the Exponential Distribution Using Maximum Ranked Set Sampling with Unequal Samples

Author(s) -

B. S. Biradar,

C. D. Santosha

Publication year - 2014

Publication title -

open journal of statistics

Language(s) - English

Resource type - Journals

eISSN - 2161-7198

pISSN - 2161-718X

DOI - 10.4236/ojs.2014.48060

Subject(s) - estimator , mathematics , statistics , rss , ranking (information retrieval) , simple random sample , efficiency , sampling (signal processing) , efficient estimator , mean squared error , minimum variance unbiased estimator , computer science , population , artificial intelligence , computer vision , operating system , demography , filter (signal processing) , sociology

Affiliation(s)\ud\ud1Department of Studies in Statistics, University of Mysore, Mysore, India.\ud2All India Institute of Speech and Hearing, Mysore, India.\udABSTRACT\ud\udIn this paper maximum ranked set sampling procedure with unequal samples (MRSSU) is proposed. Maximum likelihood estimator and modified maximum likelihood estimator are obtained and their properties are studied under exponential distribution. These methods are studied under both perfect and imperfect ranking (with errors in ranking). These estimators are then compared with estimators based on simple random sampling (SRS) and ranked set sampling (RSS) procedures. It is shown that relative efficiencies of the estimators based on MRSSU are better than those of the estimator based on SRS. Simulation results show that efficiency of proposed estimator is better than estimator based on RSS under ranking error

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