PARAMETER ESTIMATION FOR 2-PARAMETER LOG-LOGISTIC DISTRIBUTION (LLD2) BY MAXIMUM ENTROPY uri icon

abstract

  • The principle of maximum entropy (POME) was employed to derive a new method of parameter estimation for the 2-parameter log-logistic distribution (LLD2). 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). Simulation results showed that POME's performance was superior in predicting quantiles oflarge recurrence intervals when population coefficient of variation was greater than or equal to 1.0. In all other cases, POME's performance was comparable to other methods. In terms of parameter bias and root mean square error, POME was comparable to MLE and superior to both MOM and PWM. 1995, Taylor & Francis Group, LLC. All rights reserved.

published proceedings

  • Civil Engineering Systems

author list (cited authors)

  • SINGH, V. P., & GUO, H.

citation count

  • 9

complete list of authors

  • SINGH, VP||GUO, H

publication date

  • November 1995