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

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

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.

[1] S. Bennett,et al. Log‐Logistic Regression Models for Survival Data , 1983 .

[2] I. W. Burr. Cumulative Frequency Functions , 1942 .

[3] Jerald F. Lawless,et al. A note on lifetime regression models , 1986 .

[4] T. Haktanir. Statistical modelling of annual maximum flows in Turkish rivers , 1991 .

[5] M. Tribus. Rational descriptions, decisions, and designs , 1969 .

[6] M. I. Ahmad,et al. Log-logistic flood frequency analysis , 1988 .

[7] Paul W. Mielke,et al. Three-Parameter Kappa Distribution Maximum Likelihood Estimates and Likelihood Ratio Tests , 1973 .

[8] I. Good,et al. The Maximum Entropy Formalism. , 1979 .

[9] Mohamed Shoukri,et al. Sampling properties of estimators of the log‐logistic distribution with application to Canadian precipitation data , 1988 .