On the characterization of the exponential distribution by the independence of its integer and fractional parts

1990 ◽  
Vol 44 (2) ◽  
pp. 83-85 ◽  
Author(s):  
Lih–Yuan Deng ◽  
Raj S. Chhikara
Keyword(s):  
Exponential Distribution

A Characterization of the Exponential Distribution

1994 ◽  
Vol 44 (1-2) ◽  
pp. 123-126
Author(s):  
E. S. Jebvanand ◽  
N. Unnikrishnan Nair
Keyword(s):  
Exponential Distribution ◽  
Prior Distribution ◽  
Future Observation ◽  
Informative Prior ◽  
Informative Prior Distribution ◽  
Continuous Population

In this note we prove that the exponential distribution is characterized by the property [Formula: see text] where Y is a future observation and x1, x2,…, x n are identical and independently distributed observations from a continuous population with density f( x; a), where a is assumed to have a non-informative prior distribution

A characterization of the negative exponential distribution with application to reliability theory

1981 ◽  
Vol 18 (3) ◽  
pp. 652-659 ◽  
Author(s):  
M. J. Phillips
Keyword(s):  
Exponential Distribution ◽  
Random Variables ◽  
Reliability Theory ◽  
The Other ◽  
Independent Random Variables ◽  
System Availability ◽  
Failure Times ◽  
Negative Exponential Distribution ◽  
Negative Exponential

The negative exponential distribution is characterized in terms of two independent random variables. Only one of the random variables has a negative exponential distribution whilst the other can belong to a wide class of distributions. This result is then applied to two models for the reliability of a system of two modules subject to revealed and unrevealed faults to show when the models are equivalent. It is also shown, under certain conditions, that the system availability is only independent of the distribution of revealed failure times in one module when unrevealed failure times in the other module have a negative exponential distribution.

On weak convergence within the hnbue family of life distributions

1984 ◽  
Vol 21 (03) ◽  
pp. 654-660 ◽  
Author(s):  
Sujit K. Basu ◽  
Manish C. Bhattacharjee
Keyword(s):  
Weak Convergence ◽  
Exponential Distribution ◽  
Limiting Distribution ◽  
Sufficient Condition ◽  
Necessary And Sufficient Condition ◽  
Moment Sequence ◽  
Positive Order ◽  
Life Distributions ◽  
Necessary And Sufficient

We show that the HNBUE family of life distributions is closed under weak convergence and that weak convergence within this family is equivalent to convergence of each moment sequence of positive order to the corresponding moment of the limiting distribution. A necessary and sufficient condition for weak convergence to the exponential distribution is given, based on a new characterization of exponentials within the HNBUE family of life distributions.

scholarly journals Characterization of the exponential distribution by the relevation transform

1992 ◽  
Vol 29 (04) ◽  
pp. 1003-1004 ◽  
Author(s):  
K. A. Sing Lau ◽  
B. L. S. Prakasa Rao
Keyword(s):  
Exponential Distribution

The Service Time Properties of an Unreliable Server Characterize the Exponential Distribution

1994 ◽  
Vol 26 (01) ◽  
pp. 172-182 ◽  
Author(s):  
Z. Khalil ◽  
B. Dimitrov
Keyword(s):  
Exponential Distribution ◽  
Service Time ◽  
Initial Conditions ◽  
Mean Values ◽  
Unreliable Server ◽  
Service Disciplines ◽  
The Mean ◽  
Server Reliability ◽  
Preemptive Repeat Different

Consider the total service time of a job on an unreliable server under preemptive-repeat-different and preemptive-resume service disciplines. With identical initial conditions, for both cases, we notice that the distributions of the total service time under these two disciplines coincide, when the original service time (without interruptions due to server failures) is exponential and independent of the server reliability. We show that this fact under varying server reliability is a characterization of the exponential distribution. Further we show, under the same initial conditions, that the coincidence of the mean values also leads to the same characterization.

Some results involving HNBUE distributions

1986 ◽  
Vol 23 (04) ◽  
pp. 1038-1044
Author(s):  
A. P. Basu ◽  
S. N. U. A. Kirmani
Keyword(s):  
Lower Bound ◽  
Exponential Distribution ◽  
Renewal Process ◽  
Renewal Function ◽  
Underlying Distribution

A characterization of the exponential distribution in the class of all distributions which are HNBUE or HNWUE is proved. An upper (a lower) bound is obtained on the renewal function of a renewal process when the underlying distribution is HNBUE (HNWUE).

A characterization of the negative exponential distribution with application to reliability theory

1981 ◽  
Vol 18 (03) ◽  
pp. 652-659 ◽  
Author(s):  
M. J. Phillips
Keyword(s):  
Exponential Distribution ◽  
Random Variables ◽  
Reliability Theory ◽  
The Other ◽  
Independent Random Variables ◽  
System Availability ◽  
Failure Times ◽  
Negative Exponential Distribution ◽  
Negative Exponential

The negative exponential distribution is characterized in terms of two independent random variables. Only one of the random variables has a negative exponential distribution whilst the other can belong to a wide class of distributions. This result is then applied to two models for the reliability of a system of two modules subject to revealed and unrevealed faults to show when the models are equivalent. It is also shown, under certain conditions, that the system availability is only independent of the distribution of revealed failure times in one module when unrevealed failure times in the other module have a negative exponential distribution.

Variants of the Choquet–Deny theorem with applications

1997 ◽  
Vol 34 (1) ◽  
pp. 101-106 ◽  
Author(s):  
E. B. Fosam ◽  
D. N. Shanbhag
Keyword(s):  
Exponential Distribution ◽  
Type Equation ◽  
Discrete Version

A characterization of the exponential distribution based on a relevation-type equation and its discrete version are extended to the case of multidimensional spaces via variants of the Choquet–Deny theorem. Comments on some recent results in the literature are made.

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