Table of Contents Author Guidelines Submit a Manuscript
Journal of Probability and Statistics
Volume 2015, Article ID 723924, 5 pages
http://dx.doi.org/10.1155/2015/723924
Research Article

Statistical Tests for the Reciprocal of a Normal Mean with a Known Coefficient of Variation

Department of Mathematics and Statistics, Faculty of Science and Technology, Thammasat University, Pathum Thani 12121, Thailand

Received 14 September 2015; Revised 27 October 2015; Accepted 28 October 2015

Academic Editor: Aera Thavaneswaran

Copyright © 2015 Wararit Panichkitkosolkul. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. E. Lamanna, G. Romano, and C. Sgarbi, “Curvature measurements in nuclear emulsions,” Nuclear Instruments & Methods in Physics Research, vol. 187, no. 2-3, pp. 387–391, 1981. View at Publisher · View at Google Scholar · View at Scopus
  2. A. Zaman, “Estimators without moments: the case of the reciprocal of a normal mean,” Journal of Econometrics, vol. 15, no. 2, pp. 289–298, 1981. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  3. A. Zaman, “Admissibility of the maximum likelihood estimate of the reciprocal of a normal mean with a class of zero-one loss functions,” Sankhyā, vol. 47, no. 2, pp. 239–246, 1985. View at Google Scholar · View at MathSciNet
  4. C. S. Withers and S. Nadarajah, “Estimators for the inverse powers of a normal mean,” Journal of Statistical Planning and Inference, vol. 143, no. 2, pp. 441–455, 2013. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  5. K. Bhat and K. A. Rao, “On tests for a normal mean with known coefficient of variation,” International Statistical Review, vol. 75, no. 2, pp. 170–182, 2007. View at Publisher · View at Google Scholar · View at Scopus
  6. V. Brazauskas and J. Ghorai, “Estimating the common parameter of normal models with known coefficients of variation: a sensitivity study of asymptotically efficient estimators,” Journal of Statistical Computation and Simulation, vol. 77, no. 8, pp. 663–681, 2007. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  7. D. T. Searls, “A note on the use of an approximately known coefficient of variation,” The American Statistician, vol. 21, no. 3, pp. 20–21, 1967. View at Publisher · View at Google Scholar
  8. R. A. Khan, “A note on estimating the mean of a normal distribution with known coefficient of variation,” Journal of the American Statistical Association, vol. 63, no. 323, pp. 1039–1041, 1968. View at Publisher · View at Google Scholar
  9. A. T. Arnholt and J. L. Hebert, “Estimating the mean with known coefficient of variation,” The American Statistician, vol. 49, no. 4, pp. 367–369, 1995. View at Publisher · View at Google Scholar
  10. W. Srisodaphol and N. Tongmol, “Improved estimators of the mean of a normal distribution with a known coefficient of variation,” Journal of Probability and Statistics, vol. 2012, Article ID 807045, 5 pages, 2012. View at Publisher · View at Google Scholar · View at MathSciNet
  11. A. Wongkhao, S. Niwitpong, and S. Niwitpong, “Confidence interval for the inverse of a normal mean with a known coefficient of variation,” International Journal of Mathematical, Computational, Statistical, Natural and Physical Engineering, vol. 7, no. 9, pp. 877–880, 2013. View at Google Scholar
  12. S. Weerahandi, “Generalized confidence intervals,” Journal of the American Statistical Association, vol. 88, no. 423, pp. 899–905, 1993. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  13. R. Ihaka and R. Gentleman, “R: a language for data analysis and graphics,” Journal of Computational and Graphical Statistics, vol. 5, no. 3, pp. 299–314, 1996. View at Google Scholar · View at Scopus