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http://hdl.handle.net/11375/12479
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DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Balakrishnan, Narayanaswamy | en_US |
dc.contributor.author | Alzahrani, Alya | en_US |
dc.date.accessioned | 2014-06-18T16:59:47Z | - |
dc.date.available | 2014-06-18T16:59:47Z | - |
dc.date.created | 2012-09-14 | en_US |
dc.date.issued | 2012-10 | en_US |
dc.identifier.other | opendissertations/7363 | en_US |
dc.identifier.other | 8416 | en_US |
dc.identifier.other | 3322246 | en_US |
dc.identifier.uri | http://hdl.handle.net/11375/12479 | - |
dc.description.abstract | <p>Censoring arises quite often in lifetime data. Its presence may be planned or unplanned. In this project, we demonstrate progressive Type-II right censoring when the underlying distribution is log-logistic. The objective is to discuss inferential methods for the unknown parameters of the distribution based on the maximum likelihood estimation method. The Newton-Raphson method is proposed as a numerical technique to solve the pertinent non-linear equations. In addition, confidence intervals for the unknown parameters are constructed based on (i) asymptotic normality of the maximum likelihood estimates, and (ii) percentile bootstrap resampling technique. A Monte Carlo simulation study is conducted to evaluate the performance of the methods of inference developed here. Some illustrative examples are also presented.</p> | en_US |
dc.subject | Log-logistic distribution | en_US |
dc.subject | Progressive Type-II right censoring | en_US |
dc.subject | Maximum likelihood estimates | en_US |
dc.title | LIKELIHOOD INFERENCE FOR LOG-LOGISTIC DISTRIBUTION UNDER PROGRESSIVE TYPE-II RIGHT CENSORING | en_US |
dc.type | thesis | en_US |
dc.contributor.department | Mathematics and Statistics | en_US |
dc.description.degree | Master of Science (MSc) | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
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