國立虎尾科技大學 |

Analyzing dependent data with vine copulas = a practical guide with R /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Analyzing dependent data with vine copulas/ by Claudia Czado.
其他題名:	a practical guide with R /
作者:	Czado, Claudia.
出版者:	Cham :Springer International Publishing : : 2019.,
面頁冊數:	xxix, 242 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Copulas (Mathematical statistics) -
電子資源:	https://doi.org/10.1007/978-3-030-13785-4
ISBN:	9783030137854

Analyzing dependent data with vine copulas = a practical guide with R /
Czado, Claudia.

Analyzing dependent data with vine copulasa practical guide with R /[electronic resource] :by Claudia Czado. - Cham :Springer International Publishing :2019. - xxix, 242 p. :ill., digital ;24 cm. - Lecture notes in statistics,v.2220930-0325 ;. - Lecture notes in statistics ;205..

Preface -- Multivariate Distributions and Copulas -- Dependence Measures -- Bivariate Copula Classes, Their Visualization and Estimation -- Pair Copula Decompositions and Constructions -- Regular Vines -- Simulating Regular Vine Copulas and Distributions -- Parameter Estimation in Regular Vine Copulas -- Selection of Regular Vine Copula Models -- Comparing Regular Vine Copula Models -- Case Study: Dependence Among German DAX Stocks -- Recent Developments in Vine Copula Based Modeling -- Indices.

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.

ISBN: 9783030137854

Standard No.: 10.1007/978-3-030-13785-4doiSubjects--Topical Terms:

857499
Copulas (Mathematical statistics)

LC Class. No.: QA273.6 / .C933 2019

Dewey Class. No.: 519.535

Analyzing dependent data with vine copulas = a practical guide with R /
LDR:02964nam a2200337 a 4500 001 940644
003 DE-He213
005 20191101113600.0
006 m d
007 cr nn 008maaau
008 200417s2019 gw s 0 eng d
020 $a 9783030137854 $q (electronic bk.)
020 $a 9783030137847 $q (paper)
024 7 $a 10.1007/978-3-030-13785-4 $2 doi
035 $a 978-3-030-13785-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA273.6 $b .C933 2019
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 519.535 $2 23
090 $a QA273.6 $b .C998 2019
100 1 $a Czado, Claudia. $3 1227413
245 1 0 $a Analyzing dependent data with vine copulas $h [electronic resource] : $b a practical guide with R / $c by Claudia Czado.
260 $a Cham : $c 2019. $b Springer International Publishing : $b Imprint: Springer,
300 $a xxix, 242 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in statistics, $x 0930-0325 ; $v v.222
505 0 $a Preface -- Multivariate Distributions and Copulas -- Dependence Measures -- Bivariate Copula Classes, Their Visualization and Estimation -- Pair Copula Decompositions and Constructions -- Regular Vines -- Simulating Regular Vine Copulas and Distributions -- Parameter Estimation in Regular Vine Copulas -- Selection of Regular Vine Copula Models -- Comparing Regular Vine Copula Models -- Case Study: Dependence Among German DAX Stocks -- Recent Developments in Vine Copula Based Modeling -- Indices.
520 $a 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.
650 0 $a Copulas (Mathematical statistics) $3 857499
650 0 $a R (Computer program language) $3 679069
650 1 4 $a Statistical Theory and Methods. $3 671396
650 2 4 $a Statistics for Business, Management, Economics, Finance, Insurance. $3 1211158
650 2 4 $a Statistics for Life Sciences, Medicine, Health Sciences. $3 670172
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 782247
650 2 4 $a Big Data/Analytics. $3 1106909
650 2 4 $a Statistics and Computing/Statistics Programs. $3 669775
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer eBooks
830 0 $a Lecture notes in statistics ; $v 205. $3 889359
856 4 0 $u https://doi.org/10.1007/978-3-030-13785-4
950 $a Mathematics and Statistics (Springer-11649)