Document Type
Report
Source Publication Title
Technical Report 67
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.
Disciplines
Mathematics | Physical Sciences and Mathematics
Publication Date
8-1-1977
Language
English
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Dyer, Danny D.; Hensley, Onas L.; and Keating, Jerome P., "Comparison of Point Estimators of Normal Percentiles" (1977). Mathematics Technical Papers. 339.
https://mavmatrix.uta.edu/math_technicalpapers/339