Confidence Intervals for the Reciprocal of a Normal Mean with a Known Coefficient of Variation and a Restricted Parameter Space

Wararit Panichkitkosolkul

doi:10.18187/pjsor.v13i2.1627

Abstract

The natural parameter space is known to be restricted in many real applications such as engineering, sciences and social sciences. The confidence interval derived from the classical Neyman procedure is unsatisfactory in the case of a restricted parameter space. New confidence intervals for the reciprocal of a normal mean with a known coefficient of variation and a restricted parameter space are proposed in this paper. A simulation study has been conducted to compare the performance of the proposed confidence intervals.

Highlights

The reciprocal of a normal mean, defined by 1, where is the population mean, is widely used in many areas, such as experimental nuclear physics, biological sciences, agriculture and econometrics
Following the method proposed by Wang (2008), we present confidence intervals for the reciprocal of a normal mean with a known coefficient of variation when the population mean is restricted
The performances of the confidence intervals for the reciprocal of a normal mean with a known coefficient of variation and a restricted parameter space derived in the previous section were investigated through simulation studies

Summary

Introduction

The reciprocal of a normal mean, defined by 1, where is the population mean, is widely used in many areas, such as experimental nuclear physics, biological sciences, agriculture and econometrics. Two confidence intervals for the reciprocal of a normal mean with a known coefficient of variation were proposed by Wongkhao et al (2013). Panichkitkosolkul (2017) proposed the approximate confidence interval for the reciprocal of a normal population mean with a known coefficient of variation.

Results

Conclusion