International Journal of Statistics and Applied Mathematics
  • Printed Journal
  • Indexed Journal
  • Refereed Journal
  • Peer Reviewed Journal

International Journal of Statistics and Applied Mathematics

2021, Vol. 6, Issue 1, Part A

Asymptotic variance and MSE for P[Y>X] in sampling from two one-truncation parameter families


Author(s): Bhatt Milind B and Patel Shantilal R

Abstract: In this research note we have presented some of the asymptotic theorems related to two one-truncation parameter families of distributions and use them to obtained explicit expression of asymptotic variance for U-estimable parametric function or asymptotic MSE of biased estimator. Comparison of different estimators and other inferential problem such as asymptotic minimum mean square error equivariant estimator and mean square error stabilization transformation have been tacked. Asymptotic MSE and variance of well-known stress-strength model, P[Y>X] have been derived and performance of MLE and the UMVU estimator in terms of ARE and LRE have been obtained with illustrative example.
Abbreviations: UMVU; Uniformly Minimum Variance Unbiased, MLE; Maximum Likelihood Estimator, MSE; Mean Square Error, LRE; Limiting Risk Efficiency, ARE; Asymptotic Relative. _____. This work is supported by Extra Mural Research (EMR Individual Centric) Science and Engineering Research Board (SERB), New Delhi, India. File No. EMR/2016/005269. Efficiency, GUD; Generalized Uniform Distribution, pdf; probability density function, CDF; cumulative density function.


Pages: 15-23 | Views: 93 | Downloads: 12

Download Full Article: Click Here
How to cite this article:
Bhatt Milind B, Patel Shantilal R. Asymptotic variance and MSE for P[Y>X] in sampling from two one-truncation parameter families. Int J Stat Appl Math 2021;6(1):15-23.
Call for book chapter
International Journal of Statistics and Applied Mathematics