Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-10T15:39:43.577Z Has data issue: false hasContentIssue false

ORDERING PROPERTIES OF SPACINGS FROM HETEROGENEOUS GEOMETRIC SAMPLES

Published online by Cambridge University Press:  10 May 2017

Weiyong Ding
Affiliation:
School of Mathematics and Statistics, Jiangsu Normal University, Xuzhou 221116, China
Yiying Zhang
Affiliation:
Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam Road, Hong Kong
Peng Zhao
Affiliation:
School of Mathematics and Statistics, Jiangsu Normal University, Xuzhou 221116, China E-mail: zhaop@jsnu.edu.cn

Abstract

In the reliability context, the geometric distribution is a natural choice to model the lifetimes of some equipment and components when they are measured by the number of completed cycles of operation or strokes, or in case of periodic monitoring of continuous data. This paper aims at investigating how the heterogeneity among the parameters affects some characteristics such as the distribution and hazard rate functions of spacings arising from independent heterogeneous geometric random variables. First, refined representations of the distribution functions are provided for both the second spacing and sample range from heterogeneous geometric sample. Second, stochastic comparisons are carried out on the second spacings and sample ranges for two sets of independent and heterogeneous geometric random variables in the sense of the usual stochastic and hazard rate orderings. The results established here not only fill the gap on the study of stochastic properties of spacings from heterogeneous geometric samples, but also are expected to be applied in the fields of statistics and reliability.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Du, B., Zhao, P., & Balakrishnan, N. (2012). Likelihood ratio and hazard rate orderings of the maxima in two multiple-outlier geometric samples. Probability in the Engineering and Informational Sciences 26: 375391.Google Scholar
2. Jeske, D.R. & Blessinger, T. (2004). Tunable approximations for the mean and variance of the maximum of heterogeneous geometrically distributed random variables. The American Statistician 58(4): 322327.Google Scholar
3. Hardy, G.H., Littlewood, J.E., & Pólya, G. (1929). Some simple inequalities satisfied by convex function. Messenger of Mathematics 58: 145152.Google Scholar
4. Hardy, G.H., Littlewood, J.E., & Pólya, G. (1934). Inequalities. Cambridge: Cambridge University Press.Google Scholar
5. Kochar, S.C. (2012). Stochastic comparisons of order statistics and spacings: A review. ISRN Probability and Statistics, vol. 2012, Article ID 839473, 47 pages.Google Scholar
6. Kochar, S.C. & Xu, M. (2011). Stochastic comparisons of spacings from heterogeneous samples. In Wells, Martin T. and SenGupta, Ashis (eds.), Advances in directional and linear statistics. Physica-Verlag HD, pp. 113129.Google Scholar
7. Lundberg, B. (1955). Fatigue life of airplane structures. Journal of the Aeronautical Science 22: 394.Google Scholar
8. Mao, T. & Hu, T. (2010). Equivalent characterizations on ordering of order statistics and sample ranges. Probability in the Engineering and Informational Sciences 24: 245262.Google Scholar
9. Margolin, B.H. & Winokur, H.S. Jr. (1967). Exact moments of the order statistics of the geometric distribution and their relation to inverse sampling and reliability of redundant systems. Journal of the American Statistical Association 62(319): 915925.Google Scholar
10. Marshall, A.W., Olkin, I., & Arnold, B.C. (2011). Inequalities: Theory of majorization and its applications, 2nd edition. New York: Springer-Verlag.Google Scholar
11. Misra, N. & van der Meulen, E.C. (2003). On stochastic properties of m-spacings. Journal of Statistical Planning and Inference 115(2): 683697.Google Scholar
12. Shaked, M. & Shanthikumar, J.G. (2007). Stochastic orders. New York: Springer-Verlag.Google Scholar
13. Xu, M. & Hu, T. (2011). Order statistics from heterogeneous negative binomial random variables. Probability in the Engineering and Informational Sciences 25: 435448.Google Scholar