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Nonparametric Regression

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Part of the book series: Springer Series in Statistics ((SSS))

Abstract

An important question in many fields of science is the relationship between two variables, say X and Y. Regression analysis is concerned with the question of how Y (the dependent variable) can be explained by X (the independent or explanatory or regressor variable). This means a relation of the form

$$ Y = m(X) $$

, where m(●) is a function in the mathematical sense. In many cases theory does not put any restrictions on the form of m(●), i.e. theory does not say whether m(●) is linear, quadratic, increasing in X , etc.. Hence, it is up to empirical analysis to use data to find out more about m(●).

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© 2004 Springer-Verlag Berlin Heidelberg

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Härdle, W., Werwatz, A., Müller, M., Sperlich, S. (2004). Nonparametric Regression. In: Nonparametric and Semiparametric Models. Springer Series in Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17146-8_4

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  • DOI: https://doi.org/10.1007/978-3-642-17146-8_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-62076-8

  • Online ISBN: 978-3-642-17146-8

  • eBook Packages: Springer Book Archive

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