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
Bivariate Frequency Analysis of Rainfall using Copula Model
TL;DR: In this article, a bivariate frequency analysis by using three copula models is performed in which annual maximum rainfall events in 5 stations are used for frequency analysis and rainfall depth and duration are used as random variables.
Proceedings ArticleDOI
Modeling of dependence in a peer-to-peer video application
TL;DR: It is argued that the inter-arrival time and the packet length as well as the rate and the rate of transmission in a peer-to-peer IPTV session are dependent, and the rates are almost independent random variables.
Application of Signal Advance Technology to Electrophysiology
TL;DR: Signal advance (SA) detection has potential in early arrhythmia and epileptic seizure detection and intervention, and could also be used to improve the performance of neural computer interfaces, neurotherapy applications, radiation therapy and imaging.
Journal ArticleDOI
Parameter estimation of bivariate distributions in presence of outliers: an application to FGM copula
TL;DR: This article uses bivariate copula and obtains a formula for it in presence of outliers, to estimate the corresponding dependence parameter θ and the noise parameter β, using some different methods via copula function.
Journal ArticleDOI
Spatial based drought assessment: Where are we heading? A review on the current status and future.
TL;DR: In this paper , the authors present a comprehensive review of the various quantitative techniques used to assess the spatial characteristics of droughts at different spatial scales, and provide a broad overview of relevant case studies related to future drought occurrences under climate change.
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).