Parameter estimation for 3-parameter generalized pareto distribution by the principle of maximum entropy (POME) Academic Article

abstract

• The principle of maximum entropy (POME) is employed to derive a new method of parameter estimation for the 3-parameter generalized Pareto (GP) distribution. Monte Carlo simulated data are used to evaluate this method and compare it with the methods of moments (MOM), probability weighted moments (PWM), and maximum likelihood estimation (MLE). The parameter estimates yielded by the POME are either superior or comparable for high skewness. 1995 Taylor & Francis Group, LLC.

authors

• Singh, Vijay

published proceedings

• Hydrological Sciences Journal

author list (cited authors)

• SINGH, V. P., & GUO, H.

citation count

• 67

complete list of authors

• SINGH, VP||GUO, H

publication date

• April 1995

publisher

• Taylor & Francis  Publisher

published in

• Hydrological Sciences Journal  Journal

Digital Object Identifier (DOI)

• 10.1080/02626669509491402

start page

• 165

end page

• 181

volume

• 40

issue

• 2

URL

• http://dx.doi.org/10.1080/02626669509491402