A Comparison of Maximum Likelihood and Bayesian Estimators for the Three- Parameter Weibull Distribution
Maximum likelihood and Bayesian estimators are developed and compared for the three-parameter Weibull distribution. For the data analysed in the paper, the two sets of estimators are found to be very different. The reasons for this are explored, and ways of reducing the discrepancy, including repara...
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| Veröffentlicht in: | Applied Statistics 1987-01, Vol.36 (3), p.358-369 |
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| container_title | Applied Statistics |
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| creator | Smith, Richard L. Naylor, J. C. |
| description | Maximum likelihood and Bayesian estimators are developed and compared for the three-parameter Weibull distribution. For the data analysed in the paper, the two sets of estimators are found to be very different. The reasons for this are explored, and ways of reducing the discrepancy, including reparametrization, are investigated. Our overall conclusion is that there are practical advantages to the Bayesian approach. |
| doi_str_mv | 10.2307/2347795 |
| format | Article |
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Our overall conclusion is that there are practical advantages to the Bayesian approach.</description><identifier>ISSN: 0035-9254</identifier><identifier>EISSN: 1467-9876</identifier><identifier>DOI: 10.2307/2347795</identifier><identifier>CODEN: APSTAG</identifier><language>eng</language><publisher>Oxford: Royal Statistical Society</publisher><subject>Analytical estimating ; Applied sciences ; Bayesian inference ; Data sampling ; Estimators ; Exact sciences and technology ; Generalised Extreme Value distribution ; Goodness of fit ; Inference ; Maximum likelihood ; Maximum likelihood estimation ; Maximum likelihood estimators ; Nose distribution ; Operational research and scientific management ; Operational research. Management science ; Reliability theory. Replacement problems ; Sampling distributions ; Standard deviation ; Standard error ; Three‐parameter Weibull distribution ; Weakest link model</subject><ispartof>Applied Statistics, 1987-01, Vol.36 (3), p.358-369</ispartof><rights>Copyright Royal Statistical Society</rights><rights>1987 Royal Statistical Society</rights><rights>1988 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3297-1c4274fad7b10e0746b3638fcc5cf8ffe9d3492906c68fe043f31bfd5f7aeacb3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/2347795$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/2347795$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,780,784,803,832,4024,27869,27923,27924,27925,58017,58021,58250,58254</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=7488304$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Smith, Richard L.</creatorcontrib><creatorcontrib>Naylor, J. C.</creatorcontrib><title>A Comparison of Maximum Likelihood and Bayesian Estimators for the Three- Parameter Weibull Distribution</title><title>Applied Statistics</title><description>Maximum likelihood and Bayesian estimators are developed and compared for the three-parameter Weibull distribution. For the data analysed in the paper, the two sets of estimators are found to be very different. The reasons for this are explored, and ways of reducing the discrepancy, including reparametrization, are investigated. Our overall conclusion is that there are practical advantages to the Bayesian approach.</description><subject>Analytical estimating</subject><subject>Applied sciences</subject><subject>Bayesian inference</subject><subject>Data sampling</subject><subject>Estimators</subject><subject>Exact sciences and technology</subject><subject>Generalised Extreme Value distribution</subject><subject>Goodness of fit</subject><subject>Inference</subject><subject>Maximum likelihood</subject><subject>Maximum likelihood estimation</subject><subject>Maximum likelihood estimators</subject><subject>Nose distribution</subject><subject>Operational research and scientific management</subject><subject>Operational research. Management science</subject><subject>Reliability theory. Replacement problems</subject><subject>Sampling distributions</subject><subject>Standard deviation</subject><subject>Standard error</subject><subject>Three‐parameter Weibull distribution</subject><subject>Weakest link model</subject><issn>0035-9254</issn><issn>1467-9876</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1987</creationdate><recordtype>article</recordtype><sourceid>K30</sourceid><recordid>eNp1kF1LwzAUhoMoOKf4FwIKXnXmq01zOev8gIniJl6WNE1oZtvMpEX3761s6NXOzTkXD8855wXgHKMJoYhfE8o4F_EBGGGW8EikPDkEI4RoHAkSs2NwEsIKDYURG4FqCjPXrKW3wbXQGfgkv23TN3BuP3RtK-dKKNsS3siNDla2cBY628jO-QCN87CrNFxWXusIvkgvG91pD9-1Lfq6hrc2dH4YO-vaU3BkZB302a6PwdvdbJk9RPPn-8dsOo8UJYJHWDHCmZElLzDSiLOkoAlNjVKxMqkxWpSUCSJQopLUaMSoobgwZWy41FIVdAwutt61d5-9Dl2-cr1vh5U5JkIkPKYpHqirLaW8C8Frk6_98Jbf5BjlvzHmuxgH8nLnk0HJ2njZKhv-cM7SlA5XjMFki33ZWm_22fLXxSJDBBH-712FIcy9638AyeGKuQ</recordid><startdate>19870101</startdate><enddate>19870101</enddate><creator>Smith, Richard L.</creator><creator>Naylor, J. 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C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3297-1c4274fad7b10e0746b3638fcc5cf8ffe9d3492906c68fe043f31bfd5f7aeacb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1987</creationdate><topic>Analytical estimating</topic><topic>Applied sciences</topic><topic>Bayesian inference</topic><topic>Data sampling</topic><topic>Estimators</topic><topic>Exact sciences and technology</topic><topic>Generalised Extreme Value distribution</topic><topic>Goodness of fit</topic><topic>Inference</topic><topic>Maximum likelihood</topic><topic>Maximum likelihood estimation</topic><topic>Maximum likelihood estimators</topic><topic>Nose distribution</topic><topic>Operational research and scientific management</topic><topic>Operational research. Management science</topic><topic>Reliability theory. Replacement problems</topic><topic>Sampling distributions</topic><topic>Standard deviation</topic><topic>Standard error</topic><topic>Three‐parameter Weibull distribution</topic><topic>Weakest link model</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Smith, Richard L.</creatorcontrib><creatorcontrib>Naylor, J. C.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Periodicals Index Online Segment 05</collection><collection>Periodicals Index Online Segment 12</collection><collection>Periodicals Index Online Segment 28</collection><collection>Periodicals Index Online</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - West</collection><collection>Primary Sources Access (Plan D) - International</collection><collection>Primary Sources Access & Build (Plan A) - MEA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Midwest</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Northeast</collection><collection>Primary Sources Access (Plan D) - Southeast</collection><collection>Primary Sources Access (Plan D) - North Central</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Southeast</collection><collection>Primary Sources Access (Plan D) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - UK / I</collection><collection>Primary Sources Access (Plan D) - Canada</collection><collection>Primary Sources Access (Plan D) - EMEALA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - North Central</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - International</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - International</collection><collection>Primary Sources Access (Plan D) - West</collection><collection>Periodicals Index Online Segments 1-50</collection><collection>Primary Sources Access (Plan D) - APAC</collection><collection>Primary Sources Access (Plan D) - Midwest</collection><collection>Primary Sources Access (Plan D) - MEA</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - Canada</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - UK / I</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - EMEALA</collection><collection>Primary Sources Access & Build (Plan A) - APAC</collection><collection>Primary Sources Access & Build (Plan A) - Canada</collection><collection>Primary Sources Access & Build (Plan A) - West</collection><collection>Primary Sources Access & Build (Plan A) - EMEALA</collection><collection>Primary Sources Access (Plan D) - Northeast</collection><collection>Primary Sources Access & Build (Plan A) - Midwest</collection><collection>Primary Sources Access & Build (Plan A) - North Central</collection><collection>Primary Sources Access & Build (Plan A) - Northeast</collection><collection>Primary Sources Access & Build (Plan A) - South Central</collection><collection>Primary Sources Access & Build (Plan A) - Southeast</collection><collection>Primary Sources Access (Plan D) - UK / I</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - APAC</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - MEA</collection><jtitle>Applied Statistics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Smith, Richard L.</au><au>Naylor, J. C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Comparison of Maximum Likelihood and Bayesian Estimators for the Three- Parameter Weibull Distribution</atitle><jtitle>Applied Statistics</jtitle><date>1987-01-01</date><risdate>1987</risdate><volume>36</volume><issue>3</issue><spage>358</spage><epage>369</epage><pages>358-369</pages><issn>0035-9254</issn><eissn>1467-9876</eissn><coden>APSTAG</coden><abstract>Maximum likelihood and Bayesian estimators are developed and compared for the three-parameter Weibull distribution. For the data analysed in the paper, the two sets of estimators are found to be very different. The reasons for this are explored, and ways of reducing the discrepancy, including reparametrization, are investigated. Our overall conclusion is that there are practical advantages to the Bayesian approach.</abstract><cop>Oxford</cop><pub>Royal Statistical Society</pub><doi>10.2307/2347795</doi><tpages>12</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0035-9254 |
| ispartof | Applied Statistics, 1987-01, Vol.36 (3), p.358-369 |
| issn | 0035-9254 1467-9876 |
| language | eng |
| recordid | cdi_proquest_journals_1299675381 |
| source | Periodicals Index Online; JSTOR Mathematics & Statistics; EBSCOhost Business Source Complete; JSTOR Archive Collection A-Z Listing |
| subjects | Analytical estimating Applied sciences Bayesian inference Data sampling Estimators Exact sciences and technology Generalised Extreme Value distribution Goodness of fit Inference Maximum likelihood Maximum likelihood estimation Maximum likelihood estimators Nose distribution Operational research and scientific management Operational research. Management science Reliability theory. Replacement problems Sampling distributions Standard deviation Standard error Three‐parameter Weibull distribution Weakest link model |
| title | A Comparison of Maximum Likelihood and Bayesian Estimators for the Three- Parameter Weibull Distribution |
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