Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
PARAMETER ESTIMATION FOR 2-PARAMETER LOG-LOGISTIC DISTRIBUTION (LLD2) BY MAXIMUM ENTROPY
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 of large 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.
PARAMETER ESTIMATION FOR 2-PARAMETER LOG-LOGISTIC DISTRIBUTION (LLD2) BY MAXIMUM ENTROPY
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 of large 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.
PARAMETER ESTIMATION FOR 2-PARAMETER LOG-LOGISTIC DISTRIBUTION (LLD2) BY MAXIMUM ENTROPY
Singh, V. P. (Autor:in) / Guo, H. (Autor:in)
Civil Engineering and Environmental Systems ; 12 ; 343-357
01.11.1995
15 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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