(Non) Linear Regression Modeling

We 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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Year of publication:	2004
Authors:	Čížek, Pavel
Publisher:	Berlin : Humboldt-Universität zu Berlin, Center for Applied Statistics and Economics (CASE)

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Series:	Papers ; 2004,11
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	495295426 [GVK] hdl:10419/22185 [Handle] RePEc:zbw:caseps:200411 [RePEc]
Source:	EconStor

Persistent link: https://www.econbiz.de/10010296407