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

變量

畫布

Exponential Distribution,ms hydrology, is exponential (Singh, 1988). The exponential distribution is often used for frequency analysis of rainfall depth, intensity and duration, and number of rainfall events (Eagleson, 1982). It is frequently used in biology, genetics, quantum mechanics, reliability engineering, to name but a few.

啟發(fā)

Log-Extreme Value Type 1 Distribution,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.

CRANK

Methods of Parameter Estimation,5) 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.

鋼筆記下懲罰

Extreme Value Type III Distribution, 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.

antiandrogen

Renal Metabolism in Obstructive Uropathy of smallest order statistics would allow the use of the method of maximum likelihood estimation (MLE) to estimate the parameters of the beta distribution with little more effort than MOM. In multivariate cases, however, MOM would be the only practical method for parameter estimation.

guardianship

許可

蛙鳴聲

Three-Parameter Log-Logistic Distribution,rson type 3 distribution provided better fits than log-normal, Gumbel, SMEMAX, log-Boughton, and Pearson-type 3 distributions. He concurred with the findings of Ahmad, et al. (1988) as far as Turkish rivers were concerned.

Hyperplasia

Book 1998later leading to the development of the principle of maximum entropy (POME), the concept of entropy has been increasingly applied in a wide spectrum of areas, including chemistry, electronics and communications engineering, data acquisition and storage and retreival, data monitoring network design,