Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-27T08:17:53.665Z Has data issue: false hasContentIssue false

ITERATED FAILURE RATE MONOTONICITY AND ORDERING RELATIONS WITHIN GAMMA AND WEIBULL DISTRIBUTIONS

Published online by Cambridge University Press:  24 January 2018

Idir Arab
Affiliation:
CMUC, Department of Mathematics, University of Coimbra, Coimbra, Portugal E-mail:[email protected]
Paulo Eduardo Oliveira
Affiliation:
CMUC, Department of Mathematics, University of Coimbra, Coimbra, Portugal E-mail:[email protected]

Abstract

Stochastic ordering of random variables may be defined by the relative convexity of the tail functions. This has been extended to higher order stochastic orderings, by iteratively reassigning tail-weights. The actual verification of stochastic orderings is not simple, as this depends on inverting distribution functions for which there may be no explicit expression. The iterative definition of distributions, of course, contributes to make that verification even harder. We have a look at the stochastic ordering, introducing a method that allows for explicit usage, applying it to the Gamma and Weibull distributions, giving a complete description of the order of relations within each of these families.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2018 

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.Avarous, J. & Meste, M. (1989). Tailweight and life distributions. Statistics and Probabability Letters 8(4): 381387.Google Scholar
2.Barlow, R.E. & F. Proschan, F. (1975). Statistical theory of reliability and life testing. New York: Holt, Rinehart and Winston.Google Scholar
3.Belzunce, F., Candel, J., & Ruiz, J.M. (1995). Ordering of truncated distributions through concentration curves. Sankhyā 57: 375383.Google Scholar
4.Belzunce, F., Candel, J., & Ruiz, J.M. (1998). Ordering and asymptotic properties of residual income distributions. Sankhyā 60: 331348.Google Scholar
5.Boutsikas, M.V. & Vaggelatou, E. (2002). On the distance between convex-ordered random variables, with applications. Advances In Applied Probability 34(2): 349374.Google Scholar
6.Bryson, M.C. & Siddiqui, M.M. (1969). Some criteria for ageing. Journal of the American Statistical Association 64(328): 14721483.Google Scholar
7.Chandra, N.K. & Roy, D. (2001). Some results on the reversed hazard rate. Probability In The Engineering And Informational Sciences 15(1): 95102.Google Scholar
8.Chechile, R.A. (2011). Properties of reverse hazard functions. Journal of Mathematical Psychology 55(3): 203222.Google Scholar
9.Colombo, L. & Labrecciosa, P. (2012). A note on pricing with risk aversion. European Journal of Operational Research 216(1): 252254.Google Scholar
10.Deshpande, J.V., Kochar, S.C., & Singh, H. (1986). Aspects of positive ageing. Journal of Applied Probability 23(3): 748758.Google Scholar
11.Deshpande, J.V., Singh, H., Bagai, I., & Jain, K. (1990). Some partial orders describing positive ageing. Communications in Statistics Stochastic Models 6(3): 471481.Google Scholar
12.Fagiuoli, E. & Pellerey, F. (1993). New partial orderings and applications. Naval Research Logist 40: 829842.Google Scholar
13.Franco, M., Ruiz, M.C., & Ruiz, J.M. (2003). A note on closure of the ILR and DLR classes under formation of coherent systems. Statistical Papers 44(2): 279288.Google Scholar
14.Hanin, L.G. & Rachev, S.T. (1994). Mass-transshipment problems and ideal metrics. Journal of Computational and Applied Mathematics 56(1): 183196.Google Scholar
15.Hardy, G.H., Littlewood, J.E., & Pólya, G. (1952). Inequalities. Cambridge: Cambridge University Press.Google Scholar
16.Khaledi, B.E., Farsinezhadb, S., & Kochar, S.C. (2011). Stochastic comparisons of order statistics in the scale model. Journal of Statistical Planning and Inference 141(1): 276286.Google Scholar
17.Kochar, S. & Xu, M. (2011). The tail behavior of the convolutions of Gamma random variables. Journal of Statistical Planning and Inference 141(1): 418428.Google Scholar
18.Launer, R.L. (1984). Inequalities for NBUE and NWUE life distributions. Operations Research 32: 660667.Google Scholar
19.Marshall, A.W. & Olkin, I. (2007). Life Distributions. New York: Springer.Google Scholar
20.Nanda, A.K., Hazra, N.K., Al-Mutairi, D.K., & Ghitany, M.E. (2017). On some generalized ageing orderings. Communications in Statistics - Theory and Methods 46(11): 52735291.Google Scholar
21.Nanda, A.K., Singh, H., Misra, N. & Paul, P. (2003). Reliability properties of reversed residual lifetime. Communications in Statistics - Theory and Methods 32(10): 20312042.Google Scholar
22.Navarro, J. & Hernandez, P.J. (2004). How to obtain bathtub-shaped failure rate models from normal mixtures. Probability In The Engineering And Informational Sciences 18(4): 511531.Google Scholar
23.Palmer, J.A. (2003). Relative convexity. Technical Report, ECE Department, UCSD.Google Scholar
24.Pečarić, J.E., Proschan, F., & Tong, Y.L. (1992). Convex functions. Boston: Academic Press.Google Scholar
25.Rachev, S.T. & Rüschendorf, L. (1990). Approximation of sums by compound Poisson distributions with respect to stop-loss distances. Advances in Applied Probability 22(2): 350374.Google Scholar
26.Rachev, S.T. & Rüschendorf, L. (1992). A new ideal metric with applications to multivariate stable limit theorems. Probability Theory and Related Fields 94(2): 163187.Google Scholar
27.Rachev, S.T., Stoyanov, S.V., & Fabozzi, F.J. (2011). A Probability metrics approach to financial risk measures. Oxford: Wiley-Blackwell.Google Scholar
28.Rajba, T. (2014). On some relative convexities. Journal of Mathematical Analysis and Applications 411(2): 876886.Google Scholar
29.Roberts, A.W. & Varberg, D.E. (1973). Convex functions. New York, London: Academic Press.Google Scholar
30.Sengupta, D. & Deshpande, J.V. (1994). Some results on the relative ageing of two life distributions. Journal of Applied Probability 31(4): 9911003.Google Scholar
31.Shaked, S. & Shanthikumar, J.G. (2007). Stochastic orders. New York: Springer.Google Scholar
32.Veres-Ferrer, E.J. & Pavia, J.M. (2014). On the relationship between the reversed hazard rate and elasticity. Statistical Papers 55: 275284.Google Scholar