Improved Estimators of the Mean of a Normal Distribution with a Known Coefficient of Variation
This paper is to find the estimators of the mean θ for a normal distribution with mean θ and variance aθ2, a>0, θ>0. These estimators are proposed when the coefficient of variation is known. A mean square error (MSE) is a criterion to evaluate the estimators. The results show that the proposed...
Saved in:
Main Authors: | Wuttichai Srisodaphol, Noppakun Tongmol |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2012-01-01
|
Series: | Journal of Probability and Statistics |
Online Access: | http://dx.doi.org/10.1155/2012/807045 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Confidence Intervals for the Coefficient of Variation in a Normal Distribution with a Known Population Mean
by: Wararit Panichkitkosolkul
Published: (2013-01-01) -
Upper Bound of the Generalized p Value for the Population Variances of Lognormal Distributions with Known Coefficients of Variation
by: Rada Somkhuean, et al.
Published: (2017-01-01) -
Estimation of the coefficients of variation for inverse power Lomax distribution
by: Samah M. Ahmed, et al.
Published: (2024-11-01) -
Comparing Optimal Portfolio Performance Based on Skew-Normal Distribution and Skew-Laplace-Normal Distribution: A Mean-Absolute Deviation-Entropy Approach
by: Hila Rezaei, et al.
Published: (2024-06-01) -
A mean of dependent normal variables maximum
by: Agnė Burauskaitė, et al.
Published: (2004-12-01)