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Titlebook: Introductory Time Series with R; Andrew V. Metcalfe,Paul S.P. Cowpertwait Textbook 2009 Springer Science+Business Media, LLC, part of Spri

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發(fā)表于 2025-3-28 16:38:01 | 只看該作者
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發(fā)表于 2025-3-28 22:27:23 | 只看該作者
State Space Models,e world’s stock exchanges is a dramatic reminder that time series are subject to sudden changes. Another desirable feature of state space models is that they can incorporate time series of predictor variables in a straightforward manner.
43#
發(fā)表于 2025-3-29 01:25:06 | 只看該作者
Spectral Analysis, quantify exposure of personnel to vibration and repeated shocks. Many of the early applications of spectral analysis were of economic time series, and there has been recent interest in using spectral methods for economic dynamics analysis (Iacobucci and Noullez, 2005).
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發(fā)表于 2025-3-29 03:28:33 | 只看該作者
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發(fā)表于 2025-3-29 08:23:48 | 只看該作者
Paul S.P. Cowpertwait,Andrew V. Metcalfethese crucial events, this book is not an attempt at proposing a radically new way of interpreting macroeconomic phenomena, and, as a m- ter of fact, it is not even a book on macroeconomic theory. My more modest goal is to collect a number of insights derived from recent research on the role of comp
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發(fā)表于 2025-3-29 15:16:00 | 只看該作者
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發(fā)表于 2025-3-29 18:53:50 | 只看該作者
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發(fā)表于 2025-3-29 23:02:11 | 只看該作者
Paul S.P. Cowpertwait,Andrew V. Metcalfeptions regarding the nature of the policy space or the agents’ preferences. Our claim is that the study of such regularities can be based on the complementing, reduced-form, simple contest approach presented in the preceding chapter that captures the basic forces affecting the relationship between p
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發(fā)表于 2025-3-29 23:59:30 | 只看該作者
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發(fā)表于 2025-3-30 06:31:15 | 只看該作者
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