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ON ORDERINGS BETWEEN WEIGHTED SUMS OF RANDOM VARIABLES

Published online by Cambridge University Press:  10 December 2012

Tiantian Mao
Affiliation:
Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, Anhui 230026, People's Republic of China E-mail: mttiy@mail.ustc.edu.cn; panxq@mail.ustc.edu.cn; thu@ustc.edu.cn
Xiaoqing Pan
Affiliation:
Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, Anhui 230026, People's Republic of China E-mail: mttiy@mail.ustc.edu.cn; panxq@mail.ustc.edu.cn; thu@ustc.edu.cn
Taizhong Hu
Affiliation:
Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei, Anhui 230026, People's Republic of China E-mail: mttiy@mail.ustc.edu.cn; panxq@mail.ustc.edu.cn; thu@ustc.edu.cn

Abstract

Linear combinations of independent random variables have been extensively studied in the literature. Xu & Hu [21] and Pan, Xu, & Hu [16] unified the study of linear combinations of independent random variables under the general setup. This paper is a companion one of these two papers. In this paper, we will further study this topic. The results are further generalized to the cases of permutation invariant random variables and of independent but not necessarily identically distributed random variables which are ordered in the likelihood ratio or the hazard ratio order.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2013

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References

REFERENCES

1.Amiri, L., Khaledi, B.E. & Samaniego, F.J. (2011). On skewness and dispersion among convolutions of independent gamma random variables. Probability in the Engineering and Informational Sciences 25: 5569.CrossRefGoogle Scholar
2.Bock, M.E., Diaconis, P., Huffer, F.W. & Perlman, M.D. (1987). Inequalities for linear combinations of Gamma random variables. The Canadian Journal of Statistics 15: 387395.CrossRefGoogle Scholar
3.Diaconis, P. & Perlman, M.D. (1991). Bounds for tail probabilities of weighted sums of independent gamma random variables. In Block, H., Sampson, A.R. & Savits, T., (eds.), Topics in Statistical Dependence IMS Lecture Notes – Monograph Series. Hayward, CA: Institute of Mathematical Statistics, pp. 147166.Google Scholar
4.Hu, C.Y. & Lin, G.D. (2001). An inequality for the weighted sums of pairwise iid generalized Rayleigh random variables. Journal of Statistical Planning and Inference 92: 15.CrossRefGoogle Scholar
5.Ibragimov, R. (2007). Efficiency of linear estimators under heavy-tailedness: Convolutions of α-symmetric distributions. Econometric Theory 23: 501517.CrossRefGoogle Scholar
6.Karlin, S. & Rinott, Y. (1983). Comparison of measures, multivariate majorization, and applications to statistics. In Karlin, S. et al. (eds.), Studies in Econometrics, Time Series, and Multivariate Statistics. New York: Academic Press, pp. 465489.CrossRefGoogle Scholar
7.Khaledi, B.E. & Kochar, S.C. (2004). Ordering convolutions of gamma random variables. Sankhyā 66: 466473.Google Scholar
8.Kibria, B.M.G. & Nadarajah, S. (2007). Reliability modeling: Linear combination and ratio of exponential and Rayleigh. IEEE Transactions on Reliability 56: 102105.CrossRefGoogle Scholar
9.Kochar, S.C. & Xu, M. (2010). On the right spread order of convolutions of heterogeneous exponential random variables. Journal of Multivariate Analysis 101: 165176.CrossRefGoogle Scholar
10.Kochar, S.C. & Xu, M. (2011). The tail behavior of the convolutions of gamma random variables. Journal of Statistical Planning and Inference 141: 418428.CrossRefGoogle Scholar
11.Korwar, R.M. (2002). On stochastic orders for sums of independent random variables. Journal of Multivariate Analysis 80: 344357.CrossRefGoogle Scholar
12.Ma, C. (2000). Convex orders for linear combinations of random variables. Journal of Statistical Planning and Inference 84: 1125.CrossRefGoogle Scholar
13.Marshall, A.W. & Olkin, I. (1979). Inequalities: Theory of majorization and its applications. New York: Academic Press.Google Scholar
14.Müller, A. & Stoyan, D. (2002). Comparison methods for stochastic models and risks. West Sussex: John Wiley & Sons, Ltd.Google Scholar
15.Nadarajah, S. & Kotz, S. (2005). On the linear combination of exponential and gamma random variables. Entropy 7: 161171.CrossRefGoogle Scholar
16.Pan, X., Xu, M. & Hu, T. (2012). Some inequalities of linear combinations of independent random variables: II. Bernoulli, in Press.Google Scholar
17.Proschan, F. (1965). Peakedness of distributions of convex combinations. The Annals of Mathematical Statistics 36: 17031706.CrossRefGoogle Scholar
18.Righter, R. & Shanthikumar, J.G. (1992). Extension of the bivariate characterization for stochastic orders. Advances in Applied Probability 24: 506508.CrossRefGoogle Scholar
19.Shaked, M. & Shanthikumar, J.G. (2007). Stochastic orders. New York: Springer.CrossRefGoogle Scholar
20.Tong, Y.L. (1988). Some majorization inequalities in multivariate statistical analysis. SIAM Review 30: 602622.CrossRefGoogle Scholar
21.Xu, M. & Hu, T. (2011). Some inequalities of linear combinations of independent random variables: I. Journal of Applied Probability 48: 11791188.CrossRefGoogle Scholar
22.Xu, M. & Hu, T. (2012). Stochastic comparisons of capital allocations with applications. Insurance: Mathematics and Economics 50: 293298.Google Scholar
23.Yu, Y. (2011). Some stochastic inequalities for weighted sums. Bernoulli 17: 10441053.CrossRefGoogle Scholar
24.Zhao, P. (2011). Some new results on convolutions of heterogeneous gamma random variables. Journal of Multivariate Analysis 102: 958976.CrossRefGoogle Scholar
25.Zhao, P., Chan, P.S. & Ng, H.K.T. (2011). Peakness for weighted sums of symmetric random variables. Journal of Statistical Planning and Inference 141: 17371743.CrossRefGoogle Scholar