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Entropy-Based Parameter Estimation in Hydrology / Edition 1

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Overview

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.

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Editorial Reviews

From the Publisher
'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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Product Details

  • ISBN-13: 9780792352242
  • Publisher: Springer Netherlands
  • Publication date: 10/31/1998
  • Series: Water Science and Technology Library Series , #30
  • Edition description: 1998
  • Edition number: 1
  • Pages: 368
  • Product dimensions: 0.94 (w) x 6.14 (h) x 9.21 (d)

Table of Contents

preface. 1. Entropy and Principle of Maximum Entropy. 2. Methods of Parameter Estimation. 3. Uniform Distribution. 4. Exponential Distribution. 5. Normal Distribution. 6. Two-Parameter Lognormal Distribution. 7. Three-Parameter Lognormal Distribution. 8. Extreme Value Type I Distribution. 9. Log-Extreme Value Type I Distribution. 10. Extreme Value Type III Distribution. 11. Generalized Extreme Value Distribution. 12. Weibull Distribution. 13. Gamma Distribution. 14. Pearson Type III Distribution. 15. Log-Pearson Type III Distribution. 16. Beta Distribution. 17. Two-Parameter Log-Logistic Distribution. 18. Three-Parameter Log-Logistic Distribution. 19. Two-Parameter Pareto Distribution. 20. Two-Parameter Generalized Pareto Distribution. 21. Three-Parameter Generalized Pareto Distribution. 22. Two-Component Extreme Value Distribution. Subject Index.
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