國立虎尾科技大學 |

Elements of Copula Modeling with R

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Elements of Copula Modeling with R/ by Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan.
Author:	Hofert, Marius.
other author:	Kojadinovic, Ivan.
Description:	X, 267 p. 597 illus., 21 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Statistics . -
Online resource:	https://doi.org/10.1007/978-3-319-89635-9
ISBN:	9783319896359

Elements of Copula Modeling with R
Hofert, Marius.

Elements of Copula Modeling with R[electronic resource] /by Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan. - 1st ed. 2018. - X, 267 p. 597 illus., 21 illus. in color.online resource. - Use R!,2197-5736. - Use R!,.

Preface -- Introduction -- Copulas -- Classes and Families -- Estimation -- Graphical Diagnostics, Tests and Model Selection -- Ties, Time Series and Regression -- R and Package Versions -- References -- Index.

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.

ISBN: 9783319896359

Standard No.: 10.1007/978-3-319-89635-9doiSubjects--Topical Terms:

1253516
Statistics .

LC Class. No.: QA276-280

Dewey Class. No.: 330.015195

Elements of Copula Modeling with R
LDR:02571nam a22004095i 4500 001 986913
003 DE-He213
005 20200629165609.0
007 cr nn 008mamaa
008 201225s2018 gw | s |||| 0|eng d
020 $a 9783319896359 $9 978-3-319-89635-9
024 7 $a 10.1007/978-3-319-89635-9 $2 doi
035 $a 978-3-319-89635-9
050 4 $a QA276-280
072 7 $a PBT $2 bicssc
072 7 $a BUS061000 $2 bisacsh
072 7 $a PBT $2 thema
072 7 $a K $2 thema
082 0 4 $a 330.015195 $2 23
100 1 $a Hofert, Marius. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1211804
245 1 0 $a Elements of Copula Modeling with R $h [electronic resource] / $c by Marius Hofert, Ivan Kojadinovic, Martin Mächler, Jun Yan.
250 $a 1st ed. 2018.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a X, 267 p. 597 illus., 21 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Use R!, $x 2197-5736
505 0 $a Preface -- Introduction -- Copulas -- Classes and Families -- Estimation -- Graphical Diagnostics, Tests and Model Selection -- Ties, Time Series and Regression -- R and Package Versions -- References -- Index.
520 $a 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.
650 0 $a Statistics . $3 1253516
650 0 $a Economics, Mathematical . $3 1253712
650 0 $a Applied mathematics. $3 1069907
650 0 $a Engineering mathematics. $3 562757
650 0 $a Computer software. $3 528062
650 1 4 $a Statistics for Business, Management, Economics, Finance, Insurance. $3 1211158
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 782247
650 2 4 $a Statistics and Computing/Statistics Programs. $3 669775
650 2 4 $a Quantitative Finance. $3 669372
650 2 4 $a Mathematical and Computational Engineering. $3 1139415
650 2 4 $a Mathematical Software. $3 672446
700 1 $a Kojadinovic, Ivan. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1279431
700 1 $a Mächler, Martin. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1279432
700 1 $a Yan, Jun. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1279433
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319896342
776 0 8 $i Printed edition: $z 9783319896366
830 0 $a Use R!, $x 2197-5736 $3 1253869
856 4 0 $u https://doi.org/10.1007/978-3-319-89635-9
912 $a ZDB-2-SMA
912 $a ZDB-2-SXMS
950 $a Mathematics and Statistics (SpringerNature-11649)
950 $a Mathematics and Statistics (R0) (SpringerNature-43713)