Book contents
- Copulas and Their Applications in Water Resources Engineering
- Copulas and Their Applications in Water Resources Engineering
- Copyright page
- Dedication
- Contents
- Preface
- Acknowledgments
- Part One Theory
- 1 Introduction
- 2 Preliminaries
- 3 Copulas and Their Properties
- 4 Symmetric Archimedean Copulas
- 5 Asymmetric Copulas
- 6 Plackett Copula
- 7 Non-Archimedean Copulas
- 8 Entropic Copulas
- 9 Copulas in Time Series Analysis
- Part Two Applications
- Index
- References
8 - Entropic Copulas
from Part One - Theory
Published online by Cambridge University Press: 03 January 2019
Book contents
- Copulas and Their Applications in Water Resources Engineering
- Copulas and Their Applications in Water Resources Engineering
- Copyright page
- Dedication
- Contents
- Preface
- Acknowledgments
- Part One Theory
- 1 Introduction
- 2 Preliminaries
- 3 Copulas and Their Properties
- 4 Symmetric Archimedean Copulas
- 5 Asymmetric Copulas
- 6 Plackett Copula
- 7 Non-Archimedean Copulas
- 8 Entropic Copulas
- 9 Copulas in Time Series Analysis
- Part Two Applications
- Index
- References
Summary
In previous chapters, we have discussed the Archimedean and non-Archimedean copula families. In this chapter, we will introduce entropic copulas. To be more specific, we will concentrate on the entropic copulas (i.e., most entropic canonical copulas) for the bivariate case. With proper constraints (e.g., the pair rank-based correlation coefficients), the bivariate entropic copula may be easily extended to the higher dimension.
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- Copulas and their Applications in Water Resources Engineering , pp. 304 - 328Publisher: Cambridge University PressPrint publication year: 2019
References
References
Chu, B. (2011). Recovering copulas from limited information and an application to asset allocation. Journal of Banking and Finance, 35, 1824–1842. doi:10.1016/j.jbankfin.2010.12.011.CrossRefGoogle Scholar
De Michele, C., Saladori, G., Canossi, M., Petaccia, A., and Rosso, R. (2005). Bivariate statistical approach to check adequacy of dam spillway. Journal of Hydrological Engineering ASCE, 10(1), 50–57.Google Scholar
Favre, A.-C., El Adlouni, S., Perreault, L., Thiemonge, N., and Bebee, B. (2004). Multivariate hydrological frequency anlaysis using copulas. Water Resources Research, 40, W01101.Google Scholar
Hao, Z. and Singh, V. P. (2011). Single-site monthly streamflow simulation using entropy theory. Water Resource Research, 47, W09528, doi:10.1029/2100WR011419.Google Scholar
Hao, Z. and Singh, V. P. (2012). Entropy-copula method for single-site monthly streamflow simulation. Water Resources Research, 48, W06604, doi:10.1029/WR011419.Google Scholar
Jaynes, E. T. (1957). Information theory and statistical mechanics. Physical Review. Series II, 106 (4), 620–630.Google Scholar
Jaynes, E. T. (1957). Information theory and statistical mechanics II. Physical Review. Series II, 108(2), 171–190.Google Scholar
Kao, S.-H. and Govindaraju, R. S. (2007). A bivariate frequency analysis of extreme rainfall with implications for design. Journal of Geophysical Research, 112, D13119, doi:10.1029/2007JD008522.Google Scholar
Krstanovic, P. F. and Singh, V. P. (1993a). A real-time flood forecasting model based on maximum-entropy spectral analysis: I. Development. Water Resources Management, 7(2), 109–129.CrossRefGoogle Scholar
Krstanovic, P. F. and Singh, V. P. (1993b). A real-time flood forecasting model based on maximum-entropy spectral analysis: II. Application. Water Resources Management, 7(2), 131–151.Google Scholar
Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27, 379–423.Google Scholar
Singh, V.P. (1998). Entropy-Based Parameter Estimation in Hydrology. Kluwer Academic Publishers, Boston.Google Scholar
Singh, V. P. (2013). Entropy Theory in Environmental and Water Engineering. John Wiley, Sussex.Google Scholar
Singh, V. P. (2015). Entropy Theory in Hydrologic Science and Engineering. McGraw-Hill Education, New York.Google Scholar
Singh, V. P. and Krstanovic, P. F. (1987). A stochastic model for sediment yield using the principle of maximum entropy. Water Resources Research, 23(5), 781–793.Google Scholar
Singh, V. P., Zhang, L., and Rahimi, A. (2012). Probability distribution of rainfall-runoff using entropy theory. Transactions of the ASABE, 55(5), 1733–1744.Google Scholar
Vandenberghe, S., Verhoest, N. E. C., Onof, C., and De Baets, B. (2011) A comparative copula-based bivariate frequency analysis of observed and simulated storm events: a case study on Bartlett-Lewis modeled rainfall. Water Resources Research, 47, W07529, doi:10.1029/2009WR008388.Google Scholar
Zhang, L. and Singh, V. P. (2012). Bivariate rainfall and runoff analysis using entropy and copula theories. Entropy, 14, 1784–1812. doi:10.3390/e14091784.Google Scholar
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