Entropy-Based Parameter Estimation for Kappa Distribution
Academic Article
Overview
Identity
Additional Document Info
Other
View All
Overview
abstract
An entropy-based method is developed for estimating parameters of the four-parameter kappa distribution. Using four sets of data on annual maximum rainfall and on annual peak flow discharge, the entropy-based method is evaluated and compared with the methods of moments, L-moments, probability-weighted moments, and the maximum likelihood estimation. The results of estimation show that both the entropy method and the L-moment method enable the four-parameter kappa distribution to fit the data well and a combination of the two methods can further improve estimation.
