A simple exact method for testing hypotheses about the shape parameter of a log-normal distribution
The log-normal distribution is a useful lifetime distribution in many areas. The survival function of a log-normal distribution cannot be expressed in close forms. This makes it difficult to develop exact statistical methods for parameter estimation when censoring occurs. This article proposes a simple and exact method for conducting statistical tests about the shape parameter of a log-normal distribution. Necessary tables are provided based on Monte Carlo simulation. The method can be used for type II censored data. Comparing with existing exact methods, this method uses fewer tables and is easier for calculations.
Year of publication: |
1999
|
---|---|
Authors: | Chen, Zhenmin |
Published in: |
Journal of Applied Statistics. - Taylor & Francis Journals, ISSN 0266-4763. - Vol. 26.1999, 7, p. 789-805
|
Publisher: |
Taylor & Francis Journals |
Saved in:
Saved in favorites
Similar items by person
-
Joint estimation for the parameters of the extreme value distributions
Chen, Zhenmin, (1998)
-
Space-conserving agglomerative algorithms
Chen, Zhenmin, (1996)
-
Statistical inference about the shape parameter of the Weibull distribution
Chen, Zhenmin, (1997)
- More ...