Comparative Study of Ranked Set Sampling Methods under Skewed and Unskewed Distributions

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dc.contributor.advisorJeelani Bhat, M. Iqbal
dc.contributor.authorRashid, Imran
dc.date.accessioned2022-10-19T06:58:58Z
dc.date.available2022-10-19T06:58:58Z
dc.date.issued2022-10
dc.description.abstractRanked set sampling (RSS) isa special cost-effective sampling method used in situations where judgment of units can be done easily without any difficulty. The estimates based on RSS are more efficient in comparison to the traditional unrestricted sampling procedures and in recent past its modified versions have come into prominence due to their remarkable gain in efficiency inforest management research works. Inview of this the present study entitled “COMPARATIVE STUDY OF RANKED SET SAMPLING METHODS UNDER SKEWED AND UNSKEWED DISTRIBUTIONS”was carried out on skewed and unskewed distributions to evaluate the different modified versions of RSS in terms of efficiency. In order to achieve stipulated objectives simulated data wasgenerated in RStudio(version 4.1.2 -2021) utilizing Skewed and Unskewed probability distributions like gamma, exponential, uniform and normal distribution.Accordingly a ranked set sample of size150, 300, 450, 600, 750, 900, 1050, 1200 with a set size of 3,6,9,12,15,18,21,24utilizing a constant cycle (r) 50 respectively were drawn from the simulated data through different modified methods of RSS like : Extreme ranked set sampling (ERSS), Median ranked set sampling (MRSS), Percentile rank set sampling (PRSS), Balanced grouped ranked set sampling (BGRSS), Double rank set sampling (DRSS) and Truncation based rank set sampling (TBRSS)by means oflibrary( RSSampling) of R Studio. From the results it was observed that modified versions of RSS performed better in unskewed distributions in comparison to skewed distribution in terms of efficiency, asthese samples are based on modified versions of RSS which are more regularly spaced and induces stratification at sample level which involves the gain in efficiency. Also, from this study it was found thatefficiency of allmodified RSS methods increases as the sample size increases.Based on empirical investigation through simulated data, it was observed that across the modified RSS methods, Truncation based rank set sampling (TBRSS) performed better in comparison to its counterparts in terms of efficiency.Goodness of fit results revealed that the value of AIC & BIC decreased as the set size across the modified RSS methods increases, indicating that less amount of information is lostas set size increases. Finally, it is concluded that RSS has itspractical implications, where R packages facilitates a lot in implementation of modified RSS methods which are very informative and applicable to sample surveys.en_US
dc.identifier.citationPreferred for your work: Rashid, I. 2022. Comparative Study of Ranked Set Sampling Methods under Skewed and Unskewed Distributions. SKUAST- JAMMU, Chatha, India.en_US
dc.identifier.other36904
dc.identifier.urihttps://krishikosh.egranth.ac.in/handle/1/5810189171
dc.keywordsDISTRIBUTIONS, EFFICIENCY, INFORMATION CRITERIA, SIMULATION, RANKED SET, R STUDIOen_US
dc.language.isoEnglishen_US
dc.pages60en_US
dc.publisherSher-e-Kashmir University of Agricultural Sciences and Technology of Jammuen_US
dc.subStatisticsen_US
dc.themeComparative Study of Ranked Set Sampling Methods under Skewed and Unskewed Distributionsen_US
dc.these.typeM.Scen_US
dc.titleComparative Study of Ranked Set Sampling Methods under Skewed and Unskewed Distributionsen_US
dc.typeThesisen_US
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