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- Author: Umberto Cherubini
- Publisher: Springer
- ISBN-10: 3319480146
- ISBN-13: 9783319480145
- Format: 15.6 x 23.4 x 0.5 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
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Description
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.
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- Author: Umberto Cherubini
- Publisher: Springer
- ISBN-10: 3319480146
- ISBN-13: 9783319480145
- Format: 15.6 x 23.4 x 0.5 cm, minkšti viršeliai
- Language: English English
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.
Reviews