You are here

Generalized residual entropy function and its applications

Journal Name:

Publication Year:

Abstract (2. Language): 
Shannon’s entropy plays an important role in the context of the information theorey. Since, this entropy is not applicable to a system which has survived for some unit of time. So, the concept of residual entropy was developed. In this paper, we study generalized information measure for residual life time distributions and characterize some life time models based on this measure. Also, a new classes of life time distributions are defined.
30-40

REFERENCES

References: 

(1) Asaid M, Ebrahimi N (2000),“Residual entropy and its characterizations in terms of hazard
function and mean residual life time function". Statist. Prob. Lett. 49:263-269.
(2) Baig M.A.K, Dar J.G (2007),“Some new results on Renyi’s residual entropy function", to appear.
(3) Crescenzo A.D, Longobardi M (2002),“entropy based measure of uncertainty in past life time
distributions". J. of applied probability 39:434-440.
(4) Ebrahimi N(1996),“How to measure uncertainty in the life time distributions". Sankhya. vol.
58, Ser. A, 48-57.
(5) Ebrahimi N(1997), “Testing whether life time distribution is decreasing uncertainty". J.
Statist. Plann. Infer. 64:9-19.
(6) Ebrahimi N, Kirmani SNUA (1996),“Some results on ordering of survival function through
uncertainty”. Statist. Prob. Lett. 29:167-176.
(7) Belzunce F, Navarror J, Ruiz J M, Aguila Y (2004),“Some results on residual entropy function".
Metrika 59:147-161.
(8) Nair K.R.M, Rajesh G (1998),“Characterization of the probability distributions using the
residual entropy function". J. Indian Statist. Assoc. 36:157-166.
(9) Gupta R.D, Nanda A.K (2002),“ and

Thank you for copying data from http://www.arastirmax.com