Statistical inference of partially linear regression models with heteroscedastic errors

The authors study a heteroscedastic partially linear regression model and develop an inferential procedure for it. This includes a test of heteroscedasticity, a two-step estimator of the heteroscedastic variance function, semiparametric generalized least-squares estimators of the parametric and nonparametric components of the model, and a bootstrap goodness of fit test to see whether the nonparametric component can be parametrized.

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Year of publication:	2007
Authors:	You, Jinhong ; Chen, Gemai ; Zhou, Yong
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 98.2007, 8, p. 1539-1557
Publisher:	Elsevier
Keywords:	Semiparametric regression model Heteroscedasticity Local polynomial Asymptotic normality Model selection

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005093907