A Note on Estimating the Mean of a Normal Distribution with Known Coefficient of Variation

1968 ◽  
Vol 63 (323) ◽  
pp. 1039 ◽  
Author(s):  
Rasul A. Khan
Mathematics ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 831 ◽  
Author(s):  
Yousef ◽  
Hamdy

This paper considers sequentially two main problems. First, we estimate both the mean and the variance of the normal distribution under a unified one decision framework using Hall’s three-stage procedure. We consider a minimum risk point estimation problem for the variance considering a squared-error loss function with linear sampling cost. Then we construct a confidence interval for the mean with a preassigned width and coverage probability. Second, as an application, we develop Fortran codes that tackle both the point estimation and confidence interval problems for the inverse coefficient of variation using a Monte Carlo simulation. The simulation results show negative regret in the estimation of the inverse coefficient of variation, which indicates that the three-stage procedure provides better estimation than the optimal.


2013 ◽  
Vol 710 ◽  
pp. 772-774
Author(s):  
Jin Huang Wu ◽  
Jun Sheng Wang ◽  
Yi Dong Wang ◽  
Jun Wei Lei

The characteristic value of the normal parent population, such as the mean, the percentile, the percentage, the standard deviation and the coefficient of variation, are often tested in engineering. The Shapiro-Wilk test and Epps-Pulley test are established in this paper to get the characteristic value of the normal parent population, which can satisfy different practical requirements.


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