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Titlebook: Multicollinearity in linear economic models; D. Neeleman Book 1973 Springer Science+Business Media Dordrecht 1973 econometrics.regression.

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發(fā)表于 2025-3-21 16:35:42 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Multicollinearity in linear economic models
編輯D. Neeleman
視頻videohttp://file.papertrans.cn/641/640209/640209.mp4
叢書名稱Tilburg Studies in Economics
圖書封面Titlebook: Multicollinearity in linear economic models;  D. Neeleman Book 1973 Springer Science+Business Media Dordrecht 1973 econometrics.regression.
描述It was R. Frisch, who in his publications ‘Correlation and Scatter Analysis in Statistical Variables‘ (1929) and ‘Statistical Confluence Analysis by means of Complete Regression Systems‘ (1934) first pointed out the complications that arise if one applies regression analysis to variables among which several independent linear relations exist. Should these relationships be exact, then there exist two closely related solutions for this problem, viz. 1. The estimation of ‘stable‘ linear combinations of coefficients, the so-called estimable functions. 2. The dropping of the wen-known condition of unbiasedness of the estimators. This leads to minimum variance minimum bias estimators. This last solution is generalised in this book for the case of a model consisting of several equations. In econometrics however, the relations among variables are nearly always approximately linear so that one cannot apply one of the solutions mentioned above, because in that case the matrices used in these methods are, although ill-conditioned, always of full rank. Approximating these matrices by good-conditioned ones of the desired rank, it is possible to apply these estimation methods. In order to get an
出版日期Book 1973
關鍵詞econometrics; regression; regression analysis; simulation
版次1
doihttps://doi.org/10.1007/978-94-011-7486-2
isbn_softcover978-94-011-7488-6
isbn_ebook978-94-011-7486-2
copyrightSpringer Science+Business Media Dordrecht 1973
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Book 1973nnot apply one of the solutions mentioned above, because in that case the matrices used in these methods are, although ill-conditioned, always of full rank. Approximating these matrices by good-conditioned ones of the desired rank, it is possible to apply these estimation methods. In order to get an
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hat one cannot apply one of the solutions mentioned above, because in that case the matrices used in these methods are, although ill-conditioned, always of full rank. Approximating these matrices by good-conditioned ones of the desired rank, it is possible to apply these estimation methods. In order to get an978-94-011-7488-6978-94-011-7486-2
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Tilburg Studies in Economicshttp://image.papertrans.cn/n/image/640209.jpg
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978-94-011-7488-6Springer Science+Business Media Dordrecht 1973
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The Quasar Redshift Cut-Offr redshifts, which is becoming increasingly well determined. The change of the LF with cosmic time can be parameterized by luminosity evolution or luminosity-dependent density evolution. New complete surveys for high-redshift quasars by slit less spectroscopy and color selection indicate the presenc
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