Skip Navigation

Biometrika 1958 45(3-4):504-520; doi:10.1093/biomet/45.3-4.504
© 1958 by Biometrika Trust
This Article
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by MENDENHALL, W.
Right arrow Articles by HADER, R. J.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

ESTIMATION OF PARAMETERS OF MIXED EXPONENTIALLY DISTRIBUTED FAILURE TIME DISTRIBUTIONS FROM CENSORED LIFE TEST DATA*

WILLIAM MENDENHALL and R. J. HADER

North Carolina State College and Research Techniques Unit London School of Economics
North Carolina State College

Statistical methods in life testing analysis have been developed in the past primarily for the case of a single failure population. In this paper a failure population which can be divided into subpopulations, each representing a different type or cause of failure, is considered. Estimates of the population parameters are obtained in the case where the subpopulations are exponentially distributed and sampling is censored at a predetermined test termination time.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Eur Heart JHome page
L.K Newby, V Hasselblad, P.W Armstrong, F Van de Werf, D.B Mark, H.D White, E.J Topol, and R.M Califf
Time-based risk assessment after myocardial infarction. Implications for timing of discharge and applications to medical decision-making
Eur. Heart J., January 2, 2003; 24(2): 182 - 189.
[Abstract] [Full Text] [PDF]

Home page
 Stat Methods Med ResHome page
B. Everitt
An introduction to finite mixture distributions
Statistical Methods in Medical Research, June 1, 1996; 5(2): 107 - 127.
[Abstract] [PDF]


Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.