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Titlebook: Research Papers in Statistical Inference for Time Series and Related Models; Essays in Honor of M Yan Liu,Junichi Hirukawa,Yoshihide Kakiza

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書目名稱Research Papers in Statistical Inference for Time Series and Related Models
副標題Essays in Honor of M
編輯Yan Liu,Junichi Hirukawa,Yoshihide Kakizawa
視頻videohttp://file.papertrans.cn/828/827813/827813.mp4
概述Includes contributions by distinguished researchers in the field to this valuable collection.Comprises a compilation of methodologies for a wide variety of statistical models based on profound theory.
圖書封面Titlebook: Research Papers in Statistical Inference for Time Series and Related Models; Essays in Honor of M Yan Liu,Junichi Hirukawa,Yoshihide Kakiza
描述.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 methodol
出版日期Book 2023
關鍵詞Time Series Analysis; Statistical Inference; Asymptotic Theory; Estimation Theory; Statistical Hypothesi
版次1
doihttps://doi.org/10.1007/978-981-99-0803-5
isbn_softcover978-981-99-0805-9
isbn_ebook978-981-99-0803-5
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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M-Estimation in GARCH Models in the Absence of Higher-Order Moments,) model, our simulations also involve higher-order models such as GARCH(2,1) and GARCH(1,2) which so far have received relatively little attention in the literature. We also consider the case of order-misspecified models. Finally, we analyze two real financial time series datasets by fitting GARCH(1,1) or GARCH(2,1) models with our M-estimators.
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