Title Details: | |
Bayes Estimators and Minimax Estimators |
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Authors: |
Kourouklis, Stavros Petropoulos, Konstantinos Piperigkou, Violetta |
Reviewer: |
Batsidis, Apostolos |
Description: | |
Abstract: |
In this chapter, we approach the estimation of the unknown parameter θ from a different perspective compared to what we have considered so far, where θ was treated merely as a fixed but unknown real number without any inherent properties. Instead, based on the problem at hand and the prior experience or information available, we assign different levels of importance to various values of θ. This allows us to take advantage of that information to provide a better estimate of the unknown parameter. In essence, we are still concerned with the estimation of unknown parameters—the only difference being that these parameters are now considered as random variables.
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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/11419/5692 |
Bibliographic Reference: | Kourouklis, S., Petropoulos, K., & Piperigkou, V. (2015). Bayes Estimators and Minimax Estimators [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/11419/5692 |
Language: |
Greek |
Is Part of: |
Topics in Parametric Statistical Inference: estimation and confidence intervals |
Publication Origin: |
Kallipos, Open Academic Editions |