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Vol 9, No 2:

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Estimation for Two Exponential Populations Based on Joint Percentile Rank Set Sampling
M. N Patel
Abstract
Ranked set sampling (RSS) is a method of data collection that makes use of the sampler’s judgment of relative sizes of potential sample units. RSS has been shown to result in more precise estimators than simple random sampling (SRS). Several types of rank set sampling methods such as extreme ranked set sampling, double rank set sampling, median rank set sampling, percentile rank set sampling etc. are available but most of the methods are based on single sample only. The concept of joint sampling becomes useful in conducting comparative lifetime tests of products coming from different populations within the same facility. In this paper we have introduced a joint percentile rank set sampling (JPRSS) when both the samples are coming from two different production lines within the same facility. We have obtained maximum likelihood estimators and Bayes estimators for the parameters of the exponential distributions based on JPRSS. In our study we found that JPRSS performs better compared to the estimators based on usual joint simple random samples. Final
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ISSN(P) 2350-0174

ISSN(O) 2456-2378

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