Maximum likelihood estimation of the Weibull distribution with reduced bias

In this short note, we derive a new bias adjusted maximum likelihood estimate for the shape parameter of the Weibull distribution with complete data and type I censored data. The proposed estimate of the shape parameter is significantly less biased and more efficient than the corresponding maximum l...

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Bibliographic Details
Published in:Statistics and computing 2023-06, Vol.33 (3), Article 69
Main Authors: Makalic, Enes, Schmidt, Daniel F.
Format: Article
Language:English
Subjects:
Artificial Intelligence
Bias
Computer Science
Maximum likelihood estimates
Maximum likelihood estimation
Original Paper
Parameters
Probability and Statistics in Computer Science
Statistical Theory and Methods
Statistics and Computing/Statistics Programs
Weibull distribution
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Summary:In this short note, we derive a new bias adjusted maximum likelihood estimate for the shape parameter of the Weibull distribution with complete data and type I censored data. The proposed estimate of the shape parameter is significantly less biased and more efficient than the corresponding maximum likelihood estimate, while being simple to compute using existing maximum likelihood software procedures.
ISSN:0960-3174
1573-1375
DOI:10.1007/s11222-023-10236-0