國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Analyzing dependent data with vine c...

Czado, Claudia.

Analyzing dependent data with vine copulasa practical guide with R /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Analyzing dependent data with vine copulasby 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$q(electronic bk.)

Analyzing dependent data with vine copulasa 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$q(electronic bk.)

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

247625
Copulas (Mathematical statistics)

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

Dewey Class. No.: 519.535

Analyzing dependent data with vine copulasa practical guide with R /
LDR:02964nmm a2200337 a 4500 001 559050
003 DE-He213
005 20191101113600.0
006 m d
007 cr nn 008maaau
008 191219s2019 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 811705
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 : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
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 247625
650 0 $a R (Computer program language) $3 210846
650 1 4 $a Statistical Theory and Methods. $3 274054
650 2 4 $a Statistics for Business, Management, Economics, Finance, Insurance. $3 825914
650 2 4 $a Statistics for Life Sciences, Medicine, Health Sciences. $3 274067
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 348605
650 2 4 $a Big Data/Analytics. $3 742047
650 2 4 $a Statistics and Computing/Statistics Programs. $3 275710
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Lecture notes in statistics ; $v 205. $3 559233
856 4 0 $u https://doi.org/10.1007/978-3-030-13785-4
950 $a Mathematics and Statistics (Springer-11649)