Journal ArticleDOI
Everything You Always Wanted to Know about Copula Modeling but Were Afraid to Ask
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This paper presents an introduction to inference for copula models, based on rank methods, by working out in detail a small, fictitious numerical example, the various steps involved in investigating the dependence between two random variables and in modeling it using copulas.Abstract:
This paper presents an introduction to inference for copula models, based on rank methods. By working out in detail a small, fictitious numerical example, the writers exhibit the various steps involved in investigating the dependence between two random variables and in modeling it using copulas. Simple graphical tools and numerical techniques are presented for selecting an appropriate model, estimating its parameters, and checking its goodness-of-fit. A larger, realistic application of the methodology to hydrological data is then presented.read more
Citations
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Journal ArticleDOI
Probabilistic power forecast of renewable distributed generation for provision of control reserve using vine copulas
Revised Pay Adjustment Factors for HMA and Concrete Pavements
TL;DR: In this paper, the authors evaluated the influence of variations in the construction QC/QA parameters on pavement performance and provided recommendations for revising the production and placement pay adjustment factors for HMA pavements and revised pay adjustments for the ride quality of HMA and concrete pavements.
Weighted least-squares inference based on dependence coefficients for multivariate copulas
TL;DR: A weighted least-squares estimator based on dependence coefficients is considered, and its consistency and asymptotic normality are established.
Book ChapterDOI
Theory of Copula in Hydrology and Hydroclimatology
TL;DR: This chapter starts with an introduction to copulas, and basic mathematical formulations for most commonly used copulas are discussed, and illustrative examples are provided to enable the readers to carry out applications to other problems.
Posted Content
A Statistical Simulation Method for Joint Time Series of Non-stationary Hourly Wave Parameters
TL;DR: In this paper, the authors presented a new simulation method for joint time series of significant wave height, mean zero-crossing periods and a directional regime variable, based on several model components which include renewal processes, Fourier series with random coefficients, ARMA processes, copulas and regime switching.
References
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Book
An Introduction to Copulas
TL;DR: This book discusses the fundamental properties of copulas and some of their primary applications, which include the study of dependence and measures of association, and the construction of families of bivariate distributions.
Journal ArticleDOI
Non-Uniform Random Variate Generation.
B. J. T. Morgan,Luc Devroye +1 more
TL;DR: This chapter reviews the main methods for generating random variables, vectors and processes in non-uniform random variate generation, and provides information on the expected time complexity of various algorithms before addressing modern topics such as indirectly specified distributions, random processes, and Markov chain methods.
Book ChapterDOI
A Class of Statistics with Asymptotically Normal Distribution
TL;DR: In this article, the authors considered the problem of estimating a U-statistic of the population characteristic of a regular functional function, where the sum ∑″ is extended over all permutations (α 1, α m ) of different integers, 1 α≤ (αi≤ n, n).