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Titlebook: Linear Regression; Jürgen Gro? Book 2003 Springer-Verlag Berlin Heidelberg 2003 Covariance matrix.Estimator.Least Squares.Point Estimation

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發(fā)表于 2025-3-23 12:13:18 | 只看該作者
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Linear Regression978-3-642-55864-1Series ISSN 0930-0325 Series E-ISSN 2197-7186
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發(fā)表于 2025-3-23 21:15:10 | 只看該作者
Book 2003 and applicable estimator available. Nonetheless, there exists a variety of alterna- tives, proving useful in specific situations. Purpose and Scope. This book aims at presenting a comprehensive survey of different point estimation methods in linear regression, along with the the- oretical backgroun
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Regression Diagnosticsted variables, the goodness of fit, the degree of collinearity, the distribution of the errors (normality, homogeneity, uncorrelatedness), the linearity of the assumed relationship, and the influence of individual observations.
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發(fā)表于 2025-3-24 09:30:29 | 只看該作者
0930-0325 e impression that it is the only reasonable and applicable estimator available. Nonetheless, there exists a variety of alterna- tives, proving useful in specific situations. Purpose and Scope. This book aims at presenting a comprehensive survey of different point estimation methods in linear regress
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Linear Admissibilitymator for ? , supposed to be admissible within the set of all linear estimators. This guarantees that the considered alternative linear estimator is better than the ordinary least squares estimator for at least one possible value of the unknown ?. The actual chapter investigates the structure of lin
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Regression Diagnostics no substantial indications for inconsistencies and violation of model assumptions can be found. This concerns e.g. the choice and number of incorporated variables, the goodness of fit, the degree of collinearity, the distribution of the errors (normality, homogeneity, uncorrelatedness), the lineari
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