Parameter estimation for 2-parameter generalized pareto distribution by POME Academic Article

abstract

• The principle of maximum entropy (POME) was employed to derive a new method of parameter estimation for the 2-parameter generalized Pareto (GP2) distribution. Monte Carlo simulated data were 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 POME were comparable or better within certain ranges of sample size and coefficient of variation. Springer-Verlag 1997.

authors

• Singh, Vijay

published proceedings

• Stochastic Environmental Research and Risk Assessment

author list (cited authors)

• Singh, V. P., & Guo, H.

citation count

• 15

complete list of authors

• Singh, VP||Guo, H

publication date

• June 1997

publisher

• Springer Nature  Publisher

published in

• Stochastic Environmental Research and Risk Assessment  Journal

Digital Object Identifier (DOI)

• 10.1007/bf02427916

start page

• 211

end page

• 227

volume

• 11

issue

• 3

URL

• http://dx.doi.org/10.1007/bf02427916