Sensitivity of normal-based triple sampling sequential point estimation to the normality assumption

被引:10
|
作者
Yousef, A. S. [1 ,2 ,3 ]
Kimber, A. C. [1 ,2 ]
Hamdy, H. I. [3 ]
机构
[1] Univ Southampton, Sch Math, Southampton SO17 1BJ, Hants, England
[2] Southampton Stat Sci Res Inst, Southampton SO17 1BJ, Hants, England
[3] Kuwait Univ, Kuwait, Kuwait
关键词
Asymptotic relative efficiency; Kurtosis; Regret; Sampling cost; Simulation; Skewness; Squared error loss function; Taylor expansion; ASYMPTOTIC THEORY; DISTRIBUTIONS;
D O I
10.1016/j.jspi.2013.03.027
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
This paper discusses the sensitivity of the sequential normal-based triple sampling procedure for estimating the population mean to departures from normality. We assume that the underlying population has finite absolute sixth moment and find that asymptotically the behavior of the estimator and of the sample size depend on the skewness and kurtosis of the underlying distribution when using a squared error loss function with linear sampling cost. These results enable the effects of non-normality easily to be assessed both qualitatively and quantitatively. We supplement our asymptotic results with a simulation experiment to study the performance of the estimator and the sample size in a range of conditions. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:1606 / 1618
页数:13
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