Bayesian Inference in Extremes Using the Four-Parameter Kappa Distribution

Bayesian Inference in Extremes Using the Four-Parameter Kappa Distribution

Maximum likelihood estimation (MLE) of the four-parameter kappa distribution (K4D) is known to be occasionally unstable for small sample sizes and to be very sensitive to outliers. To overcome this problem, this study proposes Bayesian analysis of the K4D. Bayesian estimators are obtained by virtue...

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Bibliographic Details
Main Authors: Palakorn Seenoi, Piyapatr Busababodhin, Jeong-Soo Park
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Mathematics
Subjects:
deviance information criterion
extreme values
highest posterior density
Markov chain Monte Carlo
profile likelihood
quantile estimation
Online Access:https://www.mdpi.com/2227-7390/8/12/2180

Internet

https://www.mdpi.com/2227-7390/8/12/2180

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