Goodness-of-Fit Tests For The Weibull Distribution With Unknown Parameters And Heavy Censoring


Goodness-of-fit tests are considered for testing the two-parameters Weibull distribution based on type II censored sampling with both parameters assumed unknown. Some extremely heavy censoring levels are considered which are useful when analyzing in-service field data with a large population and a small number of failures. Critical values are obtained by Monte Carlo simulation for Kolmogorov-Smirnov, Kuiper and Cramer-von Mises type test statistics. The approximate Snedecor's F-distribution is verified for the Mann-Scheuer-Fertig test statistic. The two-sided Mann-Scheuer-Fertig test is also studied and found to be important. A power study is carried out for these four test statistics for both moderate and heavy censoring for a number of different alternative models. © 1985, Taylor & Francis Group, LLC. All rights reserved.


Mathematics and Statistics

Second Department

Geosciences and Geological and Petroleum Engineering

International Standard Serial Number (ISSN)

1563-5163; 0094-9655

Document Type

Article - Journal

Document Version


File Type





© 2023 Taylor and Francis Group; Taylor and Francis, All rights reserved.

Publication Date

01 Jan 1985