Bayes estimation in weibull distribution
dc.contributor.advisor | Vinod Kumar | |
dc.contributor.author | Joshi, Himanil | |
dc.date.accessioned | 2018-05-07T10:00:04Z | |
dc.date.available | 2018-05-07T10:00:04Z | |
dc.date.issued | 2016-06 | |
dc.description.abstract | In the present study, Bayes estimators of the parameters α and β of 2-parameter Weibull distribution and its reliability function R(t) have been obtained using 2 priors by means of Tierney and Kadane method and the results obtained are illustrated by means of several random samples generated from the above said distribution through R software and two real data sets. It is revealed that when α is known, Bayes estimate (2.0074) of β is more precise for prior 2 compared to prior 1 at α=2.0, whereas Bayes estimate (0.5138) of R(t) is more precise for prior 2 compared to prior 1 at α=1.5 and initial time t=1.2. Further when β is known, Bayes estimates (1.5100) and (0.6446) of α and reliability function R(t=1.2) respectively are more precise for prior 2 compared to prior 1 at β=3.0. In case both parameters α and β are unknown, Bayes Risks of the estimates of α and R(t) under SELF are smaller for prior 2 compared to prior 1 for first three random samples generated from Weibull distribution with parameters (α=1.5, β=2.0); (α=1.5, β=3.0) and (α=2.0, β=2.5) respectively whereas Risk of the estimate of β is smaller for Prior 1 in case of these first three samples. Moreover, for the random sample generated from Weibull distribution with α=2.5, β=2.5, the risks of the estimates of β and R(t) are smaller for prior 1 compared to prior 2 and the risk of the estimate of α is smaller for prior 2 compared to prior 1. For two real data sets, prior 2 is superior to prior 1 for obtaining Bayes estimates (5.2788 and 4.8120) of α and Bayes estimates (191.6974 and 365.9996) of β which supports the conclusions drawn from the data generated through R software. Therefore, it is safer to use prior 2 compared to prior 1 for getting Bayes estimates of parameters α and β of 2 parameter Weibull distribution. | en_US |
dc.identifier.uri | http://krishikosh.egranth.ac.in/handle/1/5810044787 | |
dc.keywords | mathematics, statistics, computer science | en_US |
dc.language.iso | en | en_US |
dc.pages | 157 | en_US |
dc.publisher | G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand) | en_US |
dc.research.problem | Statistics | en_US |
dc.sub | Statistics | |
dc.subject | null | en_US |
dc.theme | Computer Science | en_US |
dc.these.type | M.Sc | en_US |
dc.title | Bayes estimation in weibull distribution | en_US |
dc.type | Thesis | en_US |