Convolution Copula Econometrics (Paperback, 1st ed. 2016)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Statistics
Release date:	December 2016
First published:	2016
Authors:	Umberto Cherubini • Fabio Gobbi • Sabrina Mulinacci
Dimensions:	235 x 155 x 5mm (L x W x T)
Format:	Paperback
Pages:	90
Edition:	1st ed. 2016
ISBN-13:	978-3-319-48014-5
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Business & Economics > Economics > Econometrics > General Books > Science & Mathematics > Mathematics > Applied mathematics > General
LSN:	3-319-48014-6
Barcode:	9783319480145

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