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Convolution Copula Econometrics
Convolution Copula Econometrics
Knygos.lt klubas Knygos.lt nariams
110,49 €
-15%
Įprastai
129,99 €
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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 variabl…
  • Leidėjas:
  • ISBN-10: 3319480146
  • ISBN-13: 9783319480145
  • Formatas: 15.6 x 23.4 x 0.5 cm, minkšti viršeliai
  • Kalba: Anglų

Convolution Copula Econometrics (el. knyga) (skaityta knyga) | knygos.lt

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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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  • Autorius: Umberto Cherubini
  • Leidėjas:
  • ISBN-10: 3319480146
  • ISBN-13: 9783319480145
  • Formatas: 15.6 x 23.4 x 0.5 cm, minkšti viršeliai
  • Kalba: Anglų

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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