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...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
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| Series: | Journal of Probability and Statistics |
| Online Access: | http://dx.doi.org/10.1155/2012/807045 |
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| Summary: | 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 estimators have preference for asymptotic comparisons. Moreover, the estimator based on jackknife technique has preference over others proposed estimators with some simulations studies. |
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| ISSN: | 1687-952X 1687-9538 |