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Simulating Copulas

Simulating Copulas
Author: Jan-Frederik Mai
Publisher: World Scientific
Total Pages: 310
Release: 2012
Genre: Mathematics
ISBN: 1848168748

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This book provides the reader with a background on simulating copulas and multivariate distributions in general. It unifies the scattered literature on the simulation of various families of copulas (elliptical, Archimedean, Marshall-Olkin type, etc.) as well as on different construction principles (factor models, pair-copula construction, etc.). The book is self-contained and unified in presentation and can be used as a textbook for advanced undergraduate or graduate students with a firm background in stochastics. Alongside the theoretical foundation, ready-to-implement algorithms and many examples make this book a valuable tool for anyone who is applying the methodology.Errata(s)Errata (128 KB)


Simulating Copulas: Stochastic Models, Sampling Algorithms, And Applications

Simulating Copulas: Stochastic Models, Sampling Algorithms, And Applications
Author: Matthias Scherer
Publisher: World Scientific
Total Pages: 310
Release: 2012-06-26
Genre: Mathematics
ISBN: 1908977582

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This book provides the reader with a background on simulating copulas and multivariate distributions in general. It unifies the scattered literature on the simulation of various families of copulas (elliptical, Archimedean, Marshall-Olkin type, etc.) as well as on different construction principles (factor models, pair-copula construction, etc.). The book is self-contained and unified in presentation and can be used as a textbook for advanced undergraduate or graduate students with a firm background in stochastics. Alongside the theoretical foundation, ready-to-implement algorithms and many examples make this book a valuable tool for anyone who is applying the methodology.


Simulating Copulas: Stochastic Models, Sampling Algorithms, And Applications (Second Edition)

Simulating Copulas: Stochastic Models, Sampling Algorithms, And Applications (Second Edition)
Author: Scherer Matthias
Publisher: #N/A
Total Pages: 356
Release: 2017-06-07
Genre: Mathematics
ISBN: 9813149264

Download Simulating Copulas: Stochastic Models, Sampling Algorithms, And Applications (Second Edition) Book in PDF, ePub and Kindle

The book provides the background on simulating copulas and multivariate distributions in general. It unifies the scattered literature on the simulation of various families of copulas (elliptical, Archimedean, Marshall-Olkin type, etc.) as well as on different construction principles (factor models, pair-copula construction, etc.). The book is self-contained and unified in presentation and can be used as a textbook for graduate and advanced undergraduate students with a firm background in stochastics. Besides the theoretical foundation, ready-to-implement algorithms and many examples make the book a valuable tool for anyone who is applying the methodology.


Simulating Copulas

Simulating Copulas
Author: Jan-Frederik Mai
Publisher:
Total Pages: 357
Release: 2017
Genre: Copulas (Mathematical statistics)
ISBN: 9789813149250

Download Simulating Copulas Book in PDF, ePub and Kindle

This book provides the reader with a background on simulating copulas and multivariate distributions in general. It unifies the scattered literature on the simulation of various families of copulas (elliptical, Archimedean, Marshall-Olkin type, etc.) as well as on different construction principles (factor models, pair-copula construction, etc.). The book is self-contained and unified in presentation and can be used as a textbook for advanced undergraduate or graduate students with a firm background in stochastics. Alongside the theoretical foundation, ready-to-implement algorithms and many examples make this book a valuable tool for anyone who is applying the methodology.


Elements of Copula Modeling with R

Elements of Copula Modeling with R
Author: Marius Hofert
Publisher: Springer
Total Pages: 267
Release: 2019-01-09
Genre: Business & Economics
ISBN: 3319896350

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This book introduces the main theoretical findings related to copulas and shows how statistical modeling of multivariate continuous distributions using copulas can be carried out in the R statistical environment with the package copula (among others). Copulas are multivariate distribution functions with standard uniform univariate margins. They are increasingly applied to modeling dependence among random variables in fields such as risk management, actuarial science, insurance, finance, engineering, hydrology, climatology, and meteorology, to name a few. In the spirit of the Use R! series, each chapter combines key theoretical definitions or results with illustrations in R. Aimed at statisticians, actuaries, risk managers, engineers and environmental scientists wanting to learn about the theory and practice of copula modeling using R without an overwhelming amount of mathematics, the book can also be used for teaching a course on copula modeling.


Dependence Modeling with Copulas

Dependence Modeling with Copulas
Author: Harry Joe
Publisher: CRC Press
Total Pages: 479
Release: 2014-06-26
Genre: Mathematics
ISBN: 1466583231

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Dependence Modeling with Copulas covers the substantial advances that have taken place in the field during the last 15 years, including vine copula modeling of high-dimensional data. Vine copula models are constructed from a sequence of bivariate copulas. The book develops generalizations of vine copula models, including common and structured facto


Copula Modeling

Copula Modeling
Author: Pravin K. Trivedi
Publisher: Now Publishers Inc
Total Pages: 126
Release: 2007
Genre: Business & Economics
ISBN: 1601980205

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Copula Modeling explores the copula approach for econometrics modeling of joint parametric distributions. Copula Modeling demonstrates that practical implementation and estimation is relatively straightforward despite the complexity of its theoretical foundations. An attractive feature of parametrically specific copulas is that estimation and inference are based on standard maximum likelihood procedures. Thus, copulas can be estimated using desktop econometric software. This offers a substantial advantage of copulas over recently proposed simulation-based approaches to joint modeling. Copulas are useful in a variety of modeling situations including financial markets, actuarial science, and microeconometrics modeling. Copula Modeling provides practitioners and scholars with a useful guide to copula modeling with a focus on estimation and misspecification. The authors cover important theoretical foundations. Throughout, the authors use Monte Carlo experiments and simulations to demonstrate copula properties


An Introduction to Copulas

An Introduction to Copulas
Author: Roger B. Nelsen
Publisher: Springer Science & Business Media
Total Pages: 227
Release: 2013-03-09
Genre: Mathematics
ISBN: 1475730764

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Copulas are functions that join multivariate distribution functions to their one-dimensional margins. The study of copulas and their role in statistics is a new but vigorously growing field. In this book the student or practitioner of statistics and probability will find discussions of the fundamental properties of copulas and some of their primary applications. The applications include the study of dependence and measures of association, and the construction of families of bivariate distributions. With nearly a hundred examples and over 150 exercises, this book is suitable as a text or for self-study. The only prerequisite is an upper level undergraduate course in probability and mathematical statistics, although some familiarity with nonparametric statistics would be useful. Knowledge of measure-theoretic probability is not required. Roger B. Nelsen is Professor of Mathematics at Lewis & Clark College in Portland, Oregon. He is also the author of "Proofs Without Words: Exercises in Visual Thinking," published by the Mathematical Association of America.


Dependence Modeling with Copulas

Dependence Modeling with Copulas
Author: Harry Joe
Publisher: CRC Press
Total Pages: 483
Release: 2014-06-26
Genre: Mathematics
ISBN: 1466583223

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Dependence Modeling with Copulas covers the substantial advances that have taken place in the field during the last 15 years, including vine copula modeling of high-dimensional data. Vine copula models are constructed from a sequence of bivariate copulas. The book develops generalizations of vine copula models, including common and structured factor models that extend from the Gaussian assumption to copulas. It also discusses other multivariate constructions and parametric copula families that have different tail properties and presents extensive material on dependence and tail properties to assist in copula model selection. The author shows how numerical methods and algorithms for inference and simulation are important in high-dimensional copula applications. He presents the algorithms as pseudocode, illustrating their implementation for high-dimensional copula models. He also incorporates results to determine dependence and tail properties of multivariate distributions for future constructions of copula models.


Analyzing Dependent Data with Vine Copulas

Analyzing Dependent Data with Vine Copulas
Author: Claudia Czado
Publisher:
Total Pages:
Release: 2019
Genre: Copulas (Mathematical statistics)
ISBN: 9783030137861

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This textbook provides a step-by-step introduction to the class of vine copulas, their statistical inference and applications. It focuses on statistical estimation and selection methods for vine copulas in data applications. These flexible copula models can successfully accommodate any form of tail dependence and are vital to many applications in finance, insurance, hydrology, marketing, engineering, chemistry, aviation, climatology and health. The book explains the pair-copula construction principles underlying these statistical models and discusses how to perform model selection and inference. It also derives simulation algorithms and presents real-world examples to illustrate the methodological concepts. The book includes numerous exercises that facilitate and deepen readers understanding, and demonstrates how the R package VineCopula can be used to explore and build statistical dependence models from scratch. In closing, the book provides insights into recent developments and open research questions in vine copula based modeling. The book is intended for students as well as statisticians, data analysts and any other quantitatively oriented researchers who are new to the field of vine copulas. Accordingly, it provides the necessary background in multivariate statistics and copula theory for exploratory data tools, so that readers only need a basic grasp of statistics and probability.