Nonlinear Time Series Semiparametric and Nonparametric Methods

During the past two decades or so, there has been a lot of interest in both theoretical and empirical analysis of nonlinear time series data. Models and methods used have been based initially on parametric nonlinear or nonparametric time series models. Such parametric nonlinear models and relate...

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Tác giả chính: Gao, Jiti
Định dạng: Sách
Ngôn ngữ:English
Được phát hành: Chapman & Hall 2012
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Truy cập trực tuyến:http://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/30554
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spelling oai:scholar.dlu.edu.vn:DLU123456789-305542012-04-30T22:36:16Z Nonlinear Time Series Semiparametric and Nonparametric Methods Gao, Jiti Econometrics During the past two decades or so, there has been a lot of interest in both theoretical and empirical analysis of nonlinear time series data. Models and methods used have been based initially on parametric nonlinear or nonparametric time series models. Such parametric nonlinear models and related methods may be too restrictive in many cases. This leads to various nonparametric techniques being used to model nonlinear time series data. The main advantage of using nonparametric methods is that the data may be allowed to speak for themselves in the sense of determining the form of mathematical relationships between time series variables. In modelling nonlinear time series data one of the tasks is to study the structural relationship between the present observation and the history of the data set. 2012-04-26T07:50:15Z 2012-04-26T07:50:15Z 2007 Book 1‑58488‑613‑7 http://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/30554 en application/pdf Chapman & Hall
institution Thư viện Trường Đại học Đà Lạt
collection Thư viện số
language English
topic Econometrics
spellingShingle Econometrics
Gao, Jiti
Nonlinear Time Series Semiparametric and Nonparametric Methods
description During the past two decades or so, there has been a lot of interest in both theoretical and empirical analysis of nonlinear time series data. Models and methods used have been based initially on parametric nonlinear or nonparametric time series models. Such parametric nonlinear models and related methods may be too restrictive in many cases. This leads to various nonparametric techniques being used to model nonlinear time series data. The main advantage of using nonparametric methods is that the data may be allowed to speak for themselves in the sense of determining the form of mathematical relationships between time series variables. In modelling nonlinear time series data one of the tasks is to study the structural relationship between the present observation and the history of the data set.
format Book
author Gao, Jiti
author_facet Gao, Jiti
author_sort Gao, Jiti
title Nonlinear Time Series Semiparametric and Nonparametric Methods
title_short Nonlinear Time Series Semiparametric and Nonparametric Methods
title_full Nonlinear Time Series Semiparametric and Nonparametric Methods
title_fullStr Nonlinear Time Series Semiparametric and Nonparametric Methods
title_full_unstemmed Nonlinear Time Series Semiparametric and Nonparametric Methods
title_sort nonlinear time series semiparametric and nonparametric methods
publisher Chapman & Hall
publishDate 2012
url http://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/30554
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