Titlebook: Entropy-Based Parameter Estimation in Hydrology; Vijay P. Singh Book 1998 Springer Science+Business Media Dordrecht 1998 environment.envir

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Non-surgical Management of Vulvar Pain,eralization of the two-parameter log-logistic distribution. The LLD3 has been applied to frequency analysis of precipitation and streamflow data. Ahmad, et al. (1988) employed it for flood frequency analysis of annual maximum series for part of Scotland, and compared its performance with the general

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https://doi.org/10.1007/978-90-313-6622-4 and biological processes (Saksena and Johnson, 1984), reliability studies and the analysis of environmental extremes. Davison and Smith (1990) pointed out that the Pareto distribution might form the basis of a broad modeling approach to high-level exceedances. DuMouchel (1983) applied it to estimat

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Urological Tests in Clinical Practicebution is a special case of Burr’s type-XII distribution (Burr, 1942), and also a special case of the “Kappa distributions” (Mielke and Johnson, 1973), that have been applied to precipitation and streamflow data.

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Two-Parameter Log-Logistic Distribution,bution is a special case of Burr’s type-XII distribution (Burr, 1942), and also a special case of the “Kappa distributions” (Mielke and Johnson, 1973), that have been applied to precipitation and streamflow data.

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Friedrich H. Moll,Dirk Schultheiss5) maximum likelihood estimation (Douglas, et al., 1976; Sorooshian, et al., 1983; Phien and Jivajirajah, 1984); and (6) least squares method (Jones, 1971; Snyder, 1972; Bree, 1978a, 1978b). A brief review of these methods is given here.

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Christopher Chermansky,Katherine Shapiro and Nix (1975) also used MOM and MLE. Kite (1978) described both MLE and MOM for the EV III distribution Singh (1987) employed the principle of maximum entropy (POME) to estimate the EV III parameters and compared it with MOM and MLE.

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Hormone Therapy for Prostate Cancer,d Salas (1996) estimated quantiles and confidence intervals for the log-Gumbel distribution. They used the methods of moments, maximum likelihood and probability weighted moments for parameter estimation.