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dc.contributor.author | Dyer, Danny D. | en |
dc.contributor.author | Hensley, Onas L. | en |
dc.contributor.author | Keating, Jerome P. | en |
dc.date.accessioned | 2010-06-03T16:08:58Z | en |
dc.date.available | 2010-06-03T16:08:58Z | en |
dc.date.issued | 1977-08 | en |
dc.identifier.uri | http://hdl.handle.net/10106/2296 | en |
dc.description.abstract | **Please note that the full text is embargoed** ABSTRACT: There are available several point estimators of the percentiles
of a normal distribution with both mean and variance unknown. Consequently, it would seam appropriate to make a comparison among the estimators through sums "closeness to the true value" criteria. Along these lines, the concept of Pitman-closeness efficiency is introduced. Essentially, when comparing two estimators, the
Pitman-closeness efficiency gives "odds" in favor of one of the
estimators being closer to the true value than is the other in a given situation. Through the use of Pitman-closeness efficiency, this paper compares (a) the maximum likelihood estimator,
(b) the minimum variance unbissed estimator, (c) the best invariant estimator, and (d) the median unbiased estimator within a class of estimators which includes (a), (b), and (c). Mean squared
efficiency is also discussed. | en |
dc.language.iso | en_US | en |
dc.publisher | University of Texas at Arlington | en |
dc.relation.ispartofseries | Technical Report;67 | en |
dc.subject | Fatigue life | en |
dc.subject | Pitman-closeness efficiency | en |
dc.subject | Mean squared efficiency | en |
dc.subject | Point estimators | en |
dc.subject.lcsh | Statistics | en |
dc.subject.lcsh | Mathematics Research | en |
dc.title | Comparison of Point Estimators of Normal Percentiles | en |
dc.type | Technical Report | en |
dc.publisher.department | Department of Mathematics | en |
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