Weibull Distribution, Iterative Likelihood Techniques and Hydrometeorological Data

Raymond K. W. Wong Atmospheric Sciences Division, Research Council of Alberta, Edmonton, Alberta, Canada T6G 2C2

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Abstract

Rapidly converging maximum likelihood procedures for estimating and testing Weibull distribution parameters are presented, together with numerical examples of their applications. Goodness-of-fit comparisons based on nine sets of meteorological or hydrological data were made among the gamma, lognormal, three-parameter kappa and Weibull distributions. The Weibull distribution is shown to be a reasonable alternative to the other three distributions.

Abstract

Rapidly converging maximum likelihood procedures for estimating and testing Weibull distribution parameters are presented, together with numerical examples of their applications. Goodness-of-fit comparisons based on nine sets of meteorological or hydrological data were made among the gamma, lognormal, three-parameter kappa and Weibull distributions. The Weibull distribution is shown to be a reasonable alternative to the other three distributions.

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