Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-28T01:55:41.101Z Has data issue: false hasContentIssue false

A note on survival models under a Markov process

Published online by Cambridge University Press:  14 July 2016

William S. Griffith*
Affiliation:
University of Kentucky
C. Srinivasan*
Affiliation:
University of Kentucky
*
Postal address for both authors: Department of Statistics, University of Kentucky, Lexington, KY 40506, USA.
Postal address for both authors: Department of Statistics, University of Kentucky, Lexington, KY 40506, USA.

Abstract

A number of extensions of the class preservation results in the Esary, Marshall and Proschan shock model have been investigated by various authors in recent years, most recently by Ghosh and Ebrahimi. In this note, generalizations are obtained using different methods for the IFR and NBUE cases when the shocking process is a regular continuous-time Markov process with stationary transition probabilites.

Type
Short Communications
Copyright
Copyright © Applied Probability Trust 1985 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Research supported by NSF Grant MCS-8212968.

References

A-Hameed, M. S. and Proschan, F. (1973) Nonstationary shock models. Stoch. Proc. Appl. 1, 383404.Google Scholar
A-Hameed, M. S. and Proschan, F. (1975) Shock models with underlying birth process. J. Appl. Prob. 12, 1828.Google Scholar
Block, H. W. and Savits, T. H. (1978) Shock models with NBUE survival. J. Appl. Prob. 15, 621628.CrossRefGoogle Scholar
Esary, J. D., Marshall, A. W. and Proschan, F. (1973) Shock models and wear processes. Ann. Prob. 1, 627649.CrossRefGoogle Scholar
Feller, W. (1971) An Introduction to Probability Theory and its Applications , Vol. II. Wiley, New York.Google Scholar
Ghosh, M. and Ebrahimi, N. (1982) Shock models leading to increasing failure rate and decreasing mean residual life survival. J. Appl. Prob. 19, 158166.Google Scholar
Joe, H. and Proschan, F. (1980) Shock models arising from processes with stationary, independent, non-negative increments. Technical Report No. M557, Department of Statistics, Florida State University.Google Scholar
Ohi, F., Kodama, M. and Nishida, T. (1977) Stationary independent shock models and the application of shock models to system reliability analysis. Rep. Stat. Appl., JUSE 24, 181190.Google Scholar
Parzen, E. (1962) Stochastic Processes. Holden-Day, San Francisco.Google Scholar