Multivariate Tests for Time Series Models

In their earlier, companion volume, Univariate Tests for Time Series Models (No. 99 of this series), the authors laid the groundwork for the explanation of tests for univariate stochastic (random) time series models. With such analysis, an essential first question is, "Does the stochastic proce...

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Tác giả chính: Lewis-Beck, Michael S.
Định dạng: Sách
Ngôn ngữ:English
Được phát hành: Sage Publications 2012
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Truy cập trực tuyến:http://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/30566
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spelling oai:scholar.dlu.edu.vn:DLU123456789-305662012-04-27T07:33:50Z Multivariate Tests for Time Series Models Lewis-Beck, Michael S. Econometrics In their earlier, companion volume, Univariate Tests for Time Series Models (No. 99 of this series), the authors laid the groundwork for the explanation of tests for univariate stochastic (random) time series models. With such analysis, an essential first question is, "Does the stochastic process change over time?" If, for variable X, the answer is "yes," then it is nonstationary. A typical example of a nonstationary time series is United States Gross National Product (GNP), which has generally drifted upward since the 1930s (considering its more or less steadily rising mean value over the period). Upon reflection, it is obvious that many social science variables measured across time are nonstationary. Lamentably, uncritical analysis of nonstationary time series can generate spurious results. 2012-04-27T07:33:50Z 2012-04-27T07:33:50Z 1994 Book 0-8039-5440-9 http://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/30566 en application/chm Sage Publications
institution Thư viện Trường Đại học Đà Lạt
collection Thư viện số
language English
topic Econometrics
spellingShingle Econometrics
Lewis-Beck, Michael S.
Multivariate Tests for Time Series Models
description In their earlier, companion volume, Univariate Tests for Time Series Models (No. 99 of this series), the authors laid the groundwork for the explanation of tests for univariate stochastic (random) time series models. With such analysis, an essential first question is, "Does the stochastic process change over time?" If, for variable X, the answer is "yes," then it is nonstationary. A typical example of a nonstationary time series is United States Gross National Product (GNP), which has generally drifted upward since the 1930s (considering its more or less steadily rising mean value over the period). Upon reflection, it is obvious that many social science variables measured across time are nonstationary. Lamentably, uncritical analysis of nonstationary time series can generate spurious results.
format Book
author Lewis-Beck, Michael S.
author_facet Lewis-Beck, Michael S.
author_sort Lewis-Beck, Michael S.
title Multivariate Tests for Time Series Models
title_short Multivariate Tests for Time Series Models
title_full Multivariate Tests for Time Series Models
title_fullStr Multivariate Tests for Time Series Models
title_full_unstemmed Multivariate Tests for Time Series Models
title_sort multivariate tests for time series models
publisher Sage Publications
publishDate 2012
url http://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/30566
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