Research Papers in Statistical Inference for Time Series and Related Models: Essays in Honor of Masanobu Taniguchi - Tapa dura

 
9789819908028: Research Papers in Statistical Inference for Time Series and Related Models: Essays in Honor of Masanobu Taniguchi
Tapa dura
ISBN 10: 9819908027 ISBN 13: 9789819908028
Editorial: Springer, 2023

Sinopsis

This book compiles theoretical developments on statistical inference for time series and related models in honor of Masanobu Taniguchi’s 70th birthday. It covers models such as long-range dependence models, nonlinear conditionally heteroscedastic time series, locally stationary processes, integer-valued time series, Lévy Processes, complex-valued time series, categorical time series, exclusive topic models, and copula models.  Many cutting-edge methods such as empirical likelihood methods, quantile regression, portmanteau tests, rank-based inference, change-point detection, testing for the goodness-of-fit, higher-order asymptotic expansion, minimum contrast estimation, optimal transportation, and topological methods are proposed, considered, or applied to complex data based on the statistical inference for stochastic processes.

The performances of these methods are illustrated by a variety of data analyses. This collection of original papers provides the reader with comprehensive and state-of-the-art theoretical works on time series and related models. It contains deep and profound treatments of the asymptotic theory of statistical inference. In addition, many specialized methodologies based on the asymptotic theory are presented in a simple way for a wide variety of statistical models. This Festschrift finds its core audiences in statistics, signal processing, and econometrics.

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Acerca del autor

Yan Liu, Waseda University
Junichi Hirukawa, Niigata University
Yoshihide Kakizawa, Hokkaido University

De la contraportada

This book compiles theoretical developments on statistical inference for time series and related models in honor of Masanobu Taniguchi's 70th birthday. It covers models such as long-range dependence models, nonlinear conditionally heteroscedastic time series, locally stationary processes, integer-valued time series, Lévy Processes, complex-valued time series, categorical time series, exclusive topic models, and copula models.  Many cutting-edge methods such as empirical likelihood methods, quantile regression, portmanteau tests, rank-based inference, change-point detection, testing for the goodness-of-fit, higher-order asymptotic expansion, minimum contrast estimation, optimal transportation, and topological methods are proposed, considered, or applied to complex data based on the statistical inference for stochastic processes.

The performances of these methods are illustrated by a variety of data analyses. This collection of original papers provides the readerwith comprehensive and state-of-the-art theoretical works on time series and related models. It contains deep and profound treatments of the asymptotic theory of statistical inference. In addition, many specialized methodologies based on the asymptotic theory are presented in a simple way for a wide variety of statistical models. This Festschrift finds its core audiences in statistics, signal processing, and econometrics.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2023
Idioma
Inglés
ISBN 10 
9819908027
ISBN 13 
9789819908028
Encuadernación
Tapa dura
Número de páginas
610
Editor
Hirukawa Junichi, Liu Yan, Kakizawa Yoshihide
Contacto del fabricante
no disponible
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