(Non) Linear Regression Modeling
AbstractWe will study causal relationships of a known form between random variables. Given a model, we distinguish one or more dependent (endogenous) variables Y = (Y1, . . . , Yl), l ∈ N, which are explained by a model, and independent (exogenous, explanatory) variables X = (X1, . . . ,Xp), p ∈ N, which explain or predict the dependent variables by means of the model. Such relationships and models are commonly referred to as regression models. --
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Bibliographic InfoPaper provided by Humboldt-Universität Berlin, Center for Applied Statistics and Economics (CASE) in its series Papers with number 2004,11.
Date of creation: 2004
Date of revision:
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