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| Title Details: | |
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Sufficiency, Completeness, and Uniformly Minimum Variance Unbiased Estimators (UMVUEs) |
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| Authors: |
Kourouklis, Stavros Petropoulos, Konstantinos Piperigkou, Violetta |
| Reviewer: |
Batsidis, Apostolos |
| Description: | |
| Abstract: |
This chapter initially presents the concept of sufficiency and its use in the improvement of an (arbitrary) estimator. Subsequently, in combination with the property of completeness, the improved estimator is shown to be optimal among all unbiased estimators—that is, a UMVUE (Uniformly Minimum Variance Unbiased Estimator). The methodology for deriving a UMVUE through sufficiency and completeness was developed by Lehmann and Scheffé. Examples are provided for finding minimum variance estimators in various samples.
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| Linguistic Editors: |
Gyftopoulou, Ourania |
| Type: |
Chapter |
| Creation Date: | 2015 |
| Item Details: | |
| License: |
http://creativecommons.org/licenses/by-nc-nd/3.0/gr |
| Handle | http://hdl.handle.net/11419/5690 |
| Bibliographic Reference: | Kourouklis, S., Petropoulos, K., & Piperigkou, V. (2015). Sufficiency, Completeness, and Uniformly Minimum Variance Unbiased Estimators (UMVUEs) [Chapter]. In Kourouklis, S., Petropoulos, K., & Piperigkou, V. 2015. Topics in Parametric Statistical Inference: estimation and confidence intervals [Undergraduate textbook]. Kallipos, Open Academic Editions. https://hdl.handle.net/11419/5690 |
| Language: |
Greek |
| Is Part of: |
Topics in Parametric Statistical Inference: estimation and confidence intervals |
| Publication Origin: |
Kallipos, Open Academic Editions |