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Entropy-Based Parameter Estimation in Hydrology (Water Science and Technology Library)
 
 
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Entropy-Based Parameter Estimation in Hydrology (Water Science and Technology Library) [Hardcover]

V.P. Singh (Author)

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Book Description

October 31, 1998 0792352246 978-0792352242 1
The book covers entropy-based techniques for parameter estimation in hydrology. The techniques are presented for twenty distributions used in hydrology, including the distributions of the normal family, the extreme-value family, the Pareto family, and the logistic family. A comparative assessment of the entropy-based techniques is made with traditional methods of parameter estimation, such as the methods of moments, maximum likelihood estimation, probability-weighted moments, L-moments, and least squares, using field data as well as Monte Carlo simulation experiments. The book is the first attempt to comprehensively present the entropy-based techniques for most distributions of interest in hydrology. Audience: The material covered in the book will be of interest to graduate students, researchers, and teachers, as well as practitioners of agricultural engineering, civil engineering, agricultural sciences, earth sciences, environmental sciences, and forest and range sciences.

Editorial Reviews

Review

`The author must be congratulated for bringing together such a wealth of information, and for its excellent presentation. The book will become a major reference volume for the parameter estimation of the probability distribution functions applied in water science. It is a welcome contribution to water resources literature and can be nominated as a book of a year in the water science area.' Pure and Applied Geophysics, 158 (2001)

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Inside This Book (learn more)
First Sentence:
Clausius coined the term 'entropy' from the Greek meaning transformation. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
between parameters and constraints, computed frequency curves, space expansion method, increasing population skewness, one obtains the entropy function, relation between distribution parameters, hydrologic frequency analysis, probability weighted moments, flood quantile estimates, parameter estimation equations, yields the partition function, flood frequency models, relative mean error, standardized bias, plotting position formula, flood frequency analysis, regional frequency analysis, generalized pareto distribution, highest bias, extreme value type, systematic period, generalized extreme value distribution, least bias, constraints for this method, various return periods
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Journal of Hydrology, Baton Rouge, New York, John River, Louisiana State University, Eliminating the Lagrange, Completion Report, Comite River, Amite River, Technical Report, American Geophysical Union, Fort Kent, Allagash River, American Society of Civil Engineers, Annals of Mathematical Statistics, Fish River, United States, Department of Civil Engineering, Hydrological Sciences Journal, Journal of Hydraulic Engineering, Journal of the Hydraulics Division, Research Report, Yorktown Heights, Comparative Evaluation of Estimation Methods, Comparative Evaluation of Parameter Estimation Methods
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