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Parameter estimation for 3-parameter log-logistic distribution (LLD3) by Pome

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Abstract

The principle of maximum entropy (POME) was employed to derive a new method of parameter estimation for the 3-parameter log-logistic distribution (LLD3). 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 of large recurrence intervals when population skew was greater than or equal to 2.0. In all other cases, POME's performance was comparable to other methods.

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Authors and Affiliations

  1. Dept. of Civil Engineering, Louisiana State University, 70803-6405, Baton Rouge, LA, USA

    V. P. Singh, H. Guo & F. X. Yu

Authors
  1. V. P. Singh
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  2. H. Guo
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  3. F. X. Yu
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Singh, V.P., Guo, H. & Yu, F.X. Parameter estimation for 3-parameter log-logistic distribution (LLD3) by Pome. Stochastic Hydrol Hydraul 7, 163–177 (1993). https://doi.org/10.1007/BF01585596

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