ORDERING CONVOLUTIONS OF HETEROGENEOUS EXPONENTIAL AND GEOMETRIC DISTRIBUTIONS REVISITED

2010 ◽  
Vol 24 (3) ◽  
pp. 329-348 ◽  
Author(s):  
Tiantian Mao ◽  
Taizhong Hu ◽  
Peng Zhao

Let Sn(a1, …, an) be the sum of n independent exponential random variables with respective hazard rates a1, …, an or the sum of n independent geometric random variables with respective parameters a1, …, an. In this article, we investigate sufficient conditions on parameter vectors (a1, …, an) and $(a_{1}^{\ast},\ldots,a_{n}^{\ast})$ under which Sn(a1, …, an) and $S_{n}(a_{1}^{\ast},\ldots,a_{n}^{\ast})$ are ordered in terms of the increasing convex and the reversed hazard rate orders for both exponential and geometric random variables and in terms of the mean residual life order for geometric variables. For the bivariate case, all of these sufficient conditions are also necessary. These characterizations are used to compare fail-safe systems with heterogeneous exponential components in the sense of the increasing convex and the reversed hazard rate orders. The main results complement several known ones in the literature.

2015 ◽  
Vol 30 (2) ◽  
pp. 281-297 ◽  
Author(s):  
Ramesh C. Gupta

This paper deals with the mean residual life function (MRLF) and its monotonicity in the case of additive and multiplicative hazard rate models. It is shown that additive (multiplicative) hazard rate does not imply reduced (proportional) MRLF and vice versa. Necessary and sufficient conditions are obtained for the two models to hold simultaneously. In the case of non-monotonic failure rates, the location of the turning points of the MRLF is investigated in both the cases. The case of random additive and multiplicative hazard rate is also studied. The monotonicity of the mean residual life is studied along with the location of the turning points. Examples are provided to illustrate the results.


2015 ◽  
Vol 2015 ◽  
pp. 1-5 ◽  
Author(s):  
S. Ramasubramanian ◽  
P. Mahendran

L2-metric is used to find the distance between triangular fuzzy numbers. The mean and variance of a fuzzy random variable are also determined by this concept. The hazard rate is estimated and its relationship with mean residual life ordering of fuzzy random variable is investigated. Additionally, we have focused on deriving bivariate characterization of hazard rate ordering which explicitly involves pairwise interchange of two fuzzy random variablesXandY.


2010 ◽  
Vol 25 (1) ◽  
pp. 55-69 ◽  
Author(s):  
Leila Amiri ◽  
Baha-Eldin Khaledi ◽  
Francisco J. Samaniego

Let {x(1)≤···≤x(n)} denote the increasing arrangement of the components of a vector x=(x1, …, xn). A vector x∈Rn majorizes another vector y (written $\bf{x} \mathop{\succeq}\limits^{m} \bf{y}$) if $\sum_{i=1}^{j} x_{(i)} \le \sum_{i=1}^{j}y_{(i)}$ for j = 1, …, n−1 and $\sum_{i=1}^{n}x_{(i)} = \sum_{i=1}^{n}y_{(i)}$. A vector x∈R+n majorizes reciprocally another vector y∈R+n (written $\bf{x} \mathop{\succeq}\limits^{rm} \bf{y}$) if $\sum_{i=1}^{j}(1/x_{(i)}) \ge \sum_{i=1}^{j}(1/y_{(i)})$ for j = 1, …, n. Let $X_{\lambda_{i},\alpha},\,i=1,\ldots,n$, be n independent random variables such that $X_{\lambda_{i},\alpha}$ is a gamma random variable with shape parameter α≥1 and scale parameter λi, i = 1, …, n. We show that if $\lambda \mathop{\succeq}\limits^{rm} \lambda^{\ast}$, then $\sum_{i=1}^{n} X_{\lambda_{i},\alpha}$ is greater than $\sum_{i=1}^{n} X_{\lambda^{\ast}_{i},\alpha}$ according to right spread order as well as mean residual life order. We also prove that if $(1/ \lambda_{1}, \ldots ,1/ \lambda_{n}) \mathop{\succeq}\limits^{m} \succeq (1/ \lambda_{1}^{\ast}, \ldots , 1/ \lambda_{n}^{\ast})$, then $\sum_{i=1}^{n} X_{\lambda_{i}, \alpha}$ is greater than $\sum_{i=1}^{n} X_{\lambda^{\ast}_{i},\alpha}$ according to new better than used in expectation order as well as Lorenze order. These results mainly generalize the recent results of Kochar and Xu [7] and Zhao and Balakrishnan [14] from convolutions of independent exponential random variables to convolutions of independent gamma random variables with common shape parameters greater than or equal to 1.


2010 ◽  
Vol 25 (1) ◽  
pp. 71-81 ◽  
Author(s):  
Hongmei Xie ◽  
Weiwei Zhuang

The concept of generalized order statistics was introduced as a unified approach to a variety of models of ordered random variables. The purpose of this article is to establish several stochastic comparisons of simple spacings in the mean residual life and the excess wealth orders under the more general assumptions on the parameters of the models.


2008 ◽  
Vol 23 (1) ◽  
pp. 17-29 ◽  
Author(s):  
Peng Zhao ◽  
Xiaohu Li

Let X1, …, Xn be independent exponential random variables with their respective hazard rates λ1, …, λn, and let Y1, …, Yn be independent exponential random variables with common hazard rate λ. Denote by Xn:n, Yn:n and X1:n, Y1:n the corresponding maximum and minimum order statistics. Xn:n−X1:n is proved to be larger than Yn:n−Y1:n according to the usual stochastic order if and only if $\lambda \geq \left({\bar{\lambda}}^{-1}\prod\nolimits^{n}_{i=1}\lambda_{i}\right)^{{1}/{(n-1)}}$ with $\bar{\lambda}=\sum\nolimits^{n}_{i=1}\lambda_{i}/n$. Further, this usual stochastic order is strengthened to the hazard rate order for n=2. However, a counterexample reveals that this can be strengthened neither to the hazard rate order nor to the reversed hazard rate order in the general case. The main result substantially improves those related ones obtained in Kochar and Rojo and Khaledi and Kochar.


1998 ◽  
Vol 12 (4) ◽  
pp. 425-444 ◽  
Author(s):  
Mark Brown ◽  
J. George Shanthikumar

In this paper we compare the variance of functions of random variables and functionals of point processes. Specifically we give sufficient conditions on two random variables X and Y under which the variances var f(X) and var f(Y) of the function f of these random variables can be compared. For example we show that if X is smaller than Y in the shifted-up mean residual life and in the usual stochastic order, then var f(X) ≤ var f(y) for all increasing convex functions f, whenever these variances are well defined. In the context of point processes we compare the variances var Φ(M) and var Φ(N) of the functional Φ of two point processes M = {M(t), t ≥ 0} and N = {N(t), t ≥ 0}. We provide sufficient conditions under which these variances can be compared. Specifically we consider comparisons between (i) two renewal processes and between (ii) two (homogeneous or nonhomogeneous) Poisson processes. For example we show that for any nonhomogeneous Poisson process N with a rate function bounded from above by λ and from below by μ and two homogeneous Poisson processes L and M with rates λ and μ, respectively, var Φ (L) ≤ var Φ (N) ≤ var Φ (M) for any functional Φ that is increasing directionally convex in the event times, whenever these variances are well defined. This, for example, implies that if Tnis the nth event time of N, then n/λ2 ≤ var (Tn) ≤ n/μ2. Some applications of these results are given.


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