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Titlebook: Computer-Aided Introduction to Econometrics; Juan Rodriguez Poo Textbook 2003 Springer-Verlag Berlin Heidelberg 2003 Computational Methods

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書(shū)目名稱(chēng)Computer-Aided Introduction to Econometrics
編輯Juan Rodriguez Poo
視頻videohttp://file.papertrans.cn/235/234446/234446.mp4
概述Includes supplementary material:
圖書(shū)封面Titlebook: Computer-Aided Introduction to Econometrics;  Juan Rodriguez Poo Textbook 2003 Springer-Verlag Berlin Heidelberg 2003 Computational Methods
描述The advent of low cost computation has made many previously intractable econometric models empirically feasible and computational methods are now realized as an integral part of the theory..This book provides graduate students and researchers not only with a sound theoretical introduction to the topic, but allows the reader through an internet based interactive computing method to learn from theory to practice the different techniques discussed in the book. Among the theoretical issues presented are linear regression analysis, univariate time series modelling with some interesting extensions such as ARCH models and dimensionality reduction techniques..The electronic version of the book including all computational possibilites can be viewed at.http://www.xplore-stat.de/ebooks/ebooks.html.
出版日期Textbook 2003
關(guān)鍵詞Computational Methods in Econometrics; Econometrics; Linear Regression Analysis; Optimization Methods; S
版次1
doihttps://doi.org/10.1007/978-3-642-55686-9
isbn_softcover978-3-642-62901-3
isbn_ebook978-3-642-55686-9
copyrightSpringer-Verlag Berlin Heidelberg 2003
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Multivariate Linear Regression Model,us or response variable denoted by ., which depends on a set of k variables .. (. = 1,…, .), called “regressors”, “independent variables” or “explanatory variables”, and an unobservable random term called “disturbance” or “error” term. The latter includes other factors (some of them non-observable,
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Univariate Time Series Modelling, We may find time series data in a wide variety of fields: macroeconomics, finance, demographics, etc. The intrinsic nature of a time series is that its observations are ordered in time and the modelling strategies of time series must take into account this property. This does not occur with cross-s
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https://doi.org/10.1007/978-3-642-55686-9Computational Methods in Econometrics; Econometrics; Linear Regression Analysis; Optimization Methods; S
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978-3-642-62901-3Springer-Verlag Berlin Heidelberg 2003
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