Characterizations of life distributions by moments of extremes and sample mean

1994 ◽  
Vol 31 (1) ◽  
pp. 148-155 ◽  
Author(s):  
Cai Jun
Keyword(s):  
Exponential Distribution ◽  
Random Variables ◽  
Random Vectors ◽  
Life Distribution ◽  
Sample Mean ◽  
Special Cases ◽  
Partial Orderings ◽  
Life Distributions

We consider two weaker partial orderings among non-negative random variables. We derive some characterizations of the equivalence of two life distributions under the weaker orderings. These results lead to the characterizations of the equality of two non-negative random vectors in distributions by moments of extremes and sample mean. As the application of these results, we get various characterizations of the exponential distribution among HNBUE and HNWUE life distribution classes. The main results of Bhattacharjee and Sethuraman (1990), and Basu and Kirmani (1986) are special cases of these more general results.

Characterizations of life distributions by moments of extremes and sample mean

1994 ◽  
Vol 31 (01) ◽  
pp. 148-155 ◽  
Author(s):  
Cai Jun
Keyword(s):  
Exponential Distribution ◽  
Random Variables ◽  
Random Vectors ◽  
Life Distribution ◽  
Sample Mean ◽  
Special Cases ◽  
Partial Orderings ◽  
Life Distributions

We consider two weaker partial orderings among non-negative random variables. We derive some characterizations of the equivalence of two life distributions under the weaker orderings. These results lead to the characterizations of the equality of two non-negative random vectors in distributions by moments of extremes and sample mean. As the application of these results, we get various characterizations of the exponential distribution among HNBUE and HNWUE life distribution classes. The main results of Bhattacharjee and Sethuraman (1990), and Basu and Kirmani (1986) are special cases of these more general results.

Families of life distributions characterized by two moments

1990 ◽  
Vol 27 (03) ◽  
pp. 720-725 ◽  
Author(s):  
Manish C. Bhattacharjee ◽  
Jayaram Sethuraman
Keyword(s):  
Exponential Distribution ◽  
Partial Ordering ◽  
Life Distribution ◽  
Partial Orderings ◽  
Life Distributions ◽  
The Moment

We consider several classical notions of partial orderings among life distributions which have been used to describe ageing properties and tail domination. We show that if a distribution G dominates another distribution F in one of these partial orderings introduced here, and if two moments of G agree with those of F, including the moment that describes this partial ordering, then G = F. This leads to a characterization of the exponential distribution among HNBUE and HNWUE life distribution classes, and thus extends the results of Basu and Bhattacharjee (1984) and rectifies an error in that paper.

Families of life distributions characterized by two moments

1990 ◽  
Vol 27 (3) ◽  
pp. 720-725 ◽  
Author(s):  
Manish C. Bhattacharjee ◽  
Jayaram Sethuraman
Keyword(s):  
Exponential Distribution ◽  
Partial Ordering ◽  
Life Distribution ◽  
Partial Orderings ◽  
Life Distributions ◽  
The Moment

We consider several classical notions of partial orderings among life distributions which have been used to describe ageing properties and tail domination. We show that if a distribution G dominates another distribution F in one of these partial orderings introduced here, and if two moments of G agree with those of F, including the moment that describes this partial ordering, then G = F. This leads to a characterization of the exponential distribution among HNBUE and HNWUE life distribution classes, and thus extends the results of Basu and Bhattacharjee (1984) and rectifies an error in that paper.

Classes of life distributions and renewal counting process

1994 ◽  
Vol 31 (4) ◽  
pp. 1110-1115 ◽  
Author(s):  
Yi-Hau Chen
Keyword(s):  
Exponential Distribution ◽  
Counting Process ◽  
Renewal Function ◽  
Life Distribution ◽  
Renewal Counting Process ◽  
Life Distributions

We prove that if the renewal function M(t) corresponding to a life distribution F is convex (concave) then F is NBU (NWU), and hence answer two questions posed by Shaked and Zhu (1992). Moreover, based-on the renewal function, some characterizations of the exponential distribution within certain classes of life distributions are given.

Classes of life distributions and renewal counting process

1994 ◽  
Vol 31 (04) ◽  
pp. 1110-1115 ◽  
Author(s):  
Yi-Hau Chen
Keyword(s):  
Exponential Distribution ◽  
Counting Process ◽  
Renewal Function ◽  
Life Distribution ◽  
Renewal Counting Process ◽  
Life Distributions

We prove that if the renewal function M(t) corresponding to a life distribution F is convex (concave) then F is NBU (NWU), and hence answer two questions posed by Shaked and Zhu (1992). Moreover, based-on the renewal function, some characterizations of the exponential distribution within certain classes of life distributions are given.

Minimal distributions in a stochastic partial ordering and bounds for Gaussian processes

1983 ◽  
Vol 20 (03) ◽  
pp. 529-536
Author(s):  
W. J. R. Eplett
Keyword(s):  
Gaussian Process ◽  
Gaussian Processes ◽  
Partial Ordering ◽  
Boundary Crossing ◽  
Conditional Probabilities ◽  
Life Distribution ◽  
Life Distributions ◽  
Bounded Below ◽  
Crossing Probabilities

A natural requirement to impose upon the life distribution of a component is that after inspection at some randomly chosen time to check whether it is still functioning, its life distribution from the time of checking should be bounded below by some specified distribution which may be defined by external considerations. Furthermore, the life distribution should ideally be minimal in the partial ordering obtained from the conditional probabilities. We prove that these specifications provide an apparently new characterization of the DFRA class of life distributions with a corresponding result for IFRA distributions. These results may be transferred, using Slepian's lemma, to obtain bounds for the boundary crossing probabilities of a stationary Gaussian process.

Ehrenfest urn models

1965 ◽  
Vol 2 (02) ◽  
pp. 352-376 ◽  
Author(s):  
Samuel Karlin ◽  
James McGregor
Keyword(s):  
Exponential Distribution ◽  
Continuous Time ◽  
Random Variables ◽  
Independent Random Variables ◽  
Urn Models ◽  
Time Intervals ◽  
Negative Exponential Distribution ◽  
Negative Exponential ◽  
Random Times

In the Ehrenfest model with continuous time one considers two urns and N balls distributed in the urns. The system is said to be in stateiif there areiballs in urn I, N −iballs in urn II. Events occur at random times and the time intervals T between successive events are independent random variables all with the same negative exponential distributionWhen an event occurs a ball is chosen at random (each of theNballs has probability 1/Nto be chosen), removed from its urn, and then placed in urn I with probabilityp, in urn II with probabilityq= 1 −p, (0 <p< 1).

Characterizing the Exponential Law Under Laplace Order Domination

1995 ◽  
Vol 45 (3-4) ◽  
pp. 171-178 ◽  
Author(s):  
Murari Mitra ◽  
Sujit K. Basu ◽  
M. C. Bhattacharjee
Keyword(s):  
Exponential Distribution ◽  
Reliability Theory ◽  
Subject Classification ◽  
Exponential Law ◽  
Life Distributions

Interesting characterizations of the exponential distribution have been obtained in classes of life distributions important in reliability theory. The results strengthen some of the analogous conclusions already existing in the literature. AMS (1991) Subject Classification No. Primary 62NOS: Secondaey 90825. 60F99.

Fatigue Reliability Functions in Semilogarithmic Coordinates

1991 ◽  
Author(s):  
Vladimir A. Avakov
Keyword(s):  
Fatigue Life ◽  
Coordinate System ◽  
Strength Distribution ◽  
Fatigue Reliability ◽  
Life Distribution ◽  
Similar Transformation ◽  
Asymptotic Type ◽  
Life Distributions ◽  
Strength Distributions

Abstract In the previous publication [2], the transformation between fatigue life and strength distribution was established using double-logarithmic coordinate system (lnN-lnS). Here, a similar transformation is established using a semi logarithmic (lnN-S) coordinate system. With the aid of the developed orthogonal relations, lognormal, Weibull and three-parameter logweibull life distributions have been transformed into normal, asymptotic type 1 of smallest value, and three-parameter Weibull strength distributions, respectively. This procedure may be applied to other types of fatigue life distribution.

Univariate and bivariate extensions of the generalized exponential distributions

2021 ◽  
Vol 71 (6) ◽  
pp. 1581-1598
Author(s):  
Vahid Nekoukhou ◽  
Ashkan Khalifeh ◽  
Hamid Bidram
Keyword(s):  
Em Algorithm ◽  
Exponential Distribution ◽  
Bivariate Distribution ◽  
Generalized Exponential Distribution ◽  
Exponential Distributions ◽  
Unknown Parameters ◽  
Data Set ◽  
New Class ◽  
Special Cases ◽  
Univariate Distribution

Abstract The main aim of this paper is to introduce a new class of continuous generalized exponential distributions, both for the univariate and bivariate cases. This new class of distributions contains some newly developed distributions as special cases, such as the univariate and also bivariate geometric generalized exponential distribution and the exponential-discrete generalized exponential distribution. Several properties of the proposed univariate and bivariate distributions, and their physical interpretations, are investigated. The univariate distribution has four parameters, whereas the bivariate distribution has five parameters. We propose to use an EM algorithm to estimate the unknown parameters. According to extensive simulation studies, we see that the effectiveness of the proposed algorithm, and the performance is quite satisfactory. A bivariate data set is analyzed and it is observed that the proposed models and the EM algorithm work quite well in practice.

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