Additive Interactive Regression Models: Circumvention of the Curse of Dimensionality

Donald W. K. Andrews () and Yoon-Jae Whang ()

Econometric Theory, 1990, vol. 6, issue 04, pages 466-479

Abstract: This paper considers series estimators of additive interactive regression (AIR) models. AIR models are nonparametric regression models that generalize additive regression models by allowing interactions between different regressor variables. They place more restrictions on the regression function, however, than do fully nonparametric regression models. By doing so, they attempt to circumvent the curse of dimensionality that afflicts the estimation of fully non-parametric regression models.

Date: 1990
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Working Paper: Additive Interactive Regression Models: Circumvention of the Curse of Dimensionality (1989)
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Persistent link: http://EconPapers.repec.org/RePEc:cup:etheor:v:6:y:1990:i:04:p:466-479_00

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