東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Convolution Copula econometrics

Cherubini, Umberto.

Linked to FindBook

Google Book

Amazon

博客來

Convolution Copula econometrics

Record Type:	Electronic resources : Monograph/item
Title/Author:	Convolution Copula econometrics/ by Umberto Cherubini, Fabio Gobbi, Sabrina Mulinacci.
Author:	Cherubini, Umberto.
other author:	Gobbi, Fabio.
Published:	Cham :Springer International Publishing : : 2016.,
Description:	x, 90 p. :ill., digital ;24 cm.
[NT 15003449]:	Preface -- The Dynamics of Economic Variables -- Estimation of Copula Models -- Copulas and Estimation of Markov Processes -- Copula-based Markov Processes: Estimation, Mixing Properties and Long-term Behavior -- Convolution-based Processes -- Application to Interest Rates.
Contained By:	Springer eBooks
Subject:	Copulas (Mathematical statistics) -
Online resource:	http://dx.doi.org/10.1007/978-3-319-48015-2
ISBN:	9783319480152

Convolution Copula econometrics
Cherubini, Umberto.

Convolution Copula econometrics[electronic resource] /by Umberto Cherubini, Fabio Gobbi, Sabrina Mulinacci. - Cham :Springer International Publishing :2016. - x, 90 p. :ill., digital ;24 cm. - SpringerBriefs in statistics,2191-544X. - SpringerBriefs in statistics..

Preface -- The Dynamics of Economic Variables -- Estimation of Copula Models -- Copulas and Estimation of Markov Processes -- Copula-based Markov Processes: Estimation, Mixing Properties and Long-term Behavior -- Convolution-based Processes -- Application to Interest Rates.

This book presents a novel approach to time series econometrics, which studies the behavior of nonlinear stochastic processes. This approach allows for an arbitrary dependence structure in the increments and provides a generalization with respect to the standard linear independent increments assumption of classical time series models. The book offers a solution to the problem of a general semiparametric approach, which is given by a concept called C-convolution (convolution of dependent variables), and the corresponding theory of convolution-based copulas. Intended for econometrics and statistics scholars with a special interest in time series analysis and copula functions (or other nonparametric approaches), the book is also useful for doctoral students with a basic knowledge of copula functions wanting to learn about the latest research developments in the field.

ISBN: 9783319480152

Standard No.: 10.1007/978-3-319-48015-2doiSubjects--Topical Terms:

1086625
Copulas (Mathematical statistics)

LC Class. No.: QA273.6

Dewey Class. No.: 519.535

Convolution Copula econometrics
LDR:02179nmm a2200337 a 4500 001 2082605
003 DE-He213
005 20161201090704.0
006 m d
007 cr nn 008maaau
008 170717s2016 gw s 0 eng d
020 $a 9783319480152 $q (electronic bk.)
020 $a 9783319480145 $q (paper)
024 7 $a 10.1007/978-3-319-48015-2 $2 doi
035 $a 978-3-319-48015-2
040 $a GP $c GP
041 0 $a eng
050 4 $a QA273.6
072 7 $a PBT $2 bicssc
072 7 $a K $2 bicssc
072 7 $a BUS061000 $2 bisacsh
082 0 4 $a 519.535 $2 23
090 $a QA273.6 $b .C523 2016
100 1 $a Cherubini, Umberto. $3 749128
245 1 0 $a Convolution Copula econometrics $h [electronic resource] / $c by Umberto Cherubini, Fabio Gobbi, Sabrina Mulinacci.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a x, 90 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in statistics, $x 2191-544X
505 0 $a Preface -- The Dynamics of Economic Variables -- Estimation of Copula Models -- Copulas and Estimation of Markov Processes -- Copula-based Markov Processes: Estimation, Mixing Properties and Long-term Behavior -- Convolution-based Processes -- Application to Interest Rates.
520 $a This book presents a novel approach to time series econometrics, which studies the behavior of nonlinear stochastic processes. This approach allows for an arbitrary dependence structure in the increments and provides a generalization with respect to the standard linear independent increments assumption of classical time series models. The book offers a solution to the problem of a general semiparametric approach, which is given by a concept called C-convolution (convolution of dependent variables), and the corresponding theory of convolution-based copulas. Intended for econometrics and statistics scholars with a special interest in time series analysis and copula functions (or other nonparametric approaches), the book is also useful for doctoral students with a basic knowledge of copula functions wanting to learn about the latest research developments in the field.
650 0 $a Copulas (Mathematical statistics) $3 1086625
650 0 $a Econometrics. $3 542934
650 1 4 $a Statistics. $3 517247
650 2 4 $a Statistics for Business/Economics/Mathematical Finance/Insurance. $3 891081
650 2 4 $a Probability Theory and Stochastic Processes. $3 891080
650 2 4 $a Statistical Theory and Methods. $3 891074
650 2 4 $a Applications of Mathematics. $3 890893
700 1 $a Gobbi, Fabio. $3 3206201
700 1 $a Mulinacci, Sabrina. $3 2156840
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a SpringerBriefs in statistics. $3 1565658
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-48015-2
950 $a Mathematics and Statistics (Springer-11649)