# (Non) linear regression modelling

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

### Abstract

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.
Original language English Handbook of Computational Statistics - 2nd Edition J.E. Gentle, W.K. Hardle, Y. Mori Heidelberg Springer Verlag 645-680 9783642215 Published - 2012

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Nonlinear Regression
Modeling
Dependent
Model
Regression Model
Random variable
Predict
Relationships

### Cite this

Cizek, P. (2012). (Non) linear regression modelling. In J. E. Gentle, W. K. Hardle, & Y. Mori (Eds.), Handbook of Computational Statistics - 2nd Edition (pp. 645-680). Heidelberg: Springer Verlag.
Cizek, P. / (Non) linear regression modelling. Handbook of Computational Statistics - 2nd Edition. editor / J.E. Gentle ; W.K. Hardle ; Y. Mori. Heidelberg : Springer Verlag, 2012. pp. 645-680
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title = "(Non) linear regression modelling",
abstract = "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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Cizek, P 2012, (Non) linear regression modelling. in JE Gentle, WK Hardle & Y Mori (eds), Handbook of Computational Statistics - 2nd Edition. Springer Verlag, Heidelberg, pp. 645-680.
Handbook of Computational Statistics - 2nd Edition. ed. / J.E. Gentle; W.K. Hardle; Y. Mori. Heidelberg : Springer Verlag, 2012. p. 645-680.

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

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AB - 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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Cizek P. (Non) linear regression modelling. In Gentle JE, Hardle WK, Mori Y, editors, Handbook of Computational Statistics - 2nd Edition. Heidelberg: Springer Verlag. 2012. p. 645-680