Statistical inference of partially linear regression models with heteroscedastic errors
AbstractThe 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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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Multivariate Analysis.
Volume (Year): 98 (2007)
Issue (Month): 8 (September)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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- Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.
- Shi, Jian & Lau, Tai-Shing, 2000. "Empirical Likelihood for Partially Linear Models," Journal of Multivariate Analysis, Elsevier, vol. 72(1), pages 132-148, January.
- Jianqing Fan & Runze Li, 2004. "New Estimation and Model Selection Procedures for Semiparametric Modeling in Longitudinal Data Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 710-723, January.
- Akdeniz Duran, Esra & Härdle, Wolfgang Karl & Osipenko, Maria, 2012.
"Difference based ridge and Liu type estimators in semiparametric regression models,"
Journal of Multivariate Analysis,
Elsevier, vol. 105(1), pages 164-175.
- Esra Akdeniz Duran & Wolfgang Karl Härdle & Maria Osipenko, 2011. "Difference based Ridge and Liu type Estimators in Semiparametric Regression Models," SFB 649 Discussion Papers SFB649DP2011-014, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Jing-Jing Zhang & Han-Ying Liang & Amei Amei, 2014. "Asymptotic normality of estimators in heteroscedastic errors-in-variables model," AStA Advances in Statistical Analysis, Springer, vol. 98(2), pages 165-195, April.
- Shen, Si-Lian & Cui, Jian-Ling & Mei, Chang-Lin & Wang, Chun-Wei, 2014. "Estimation and inference of semi-varying coefficient models with heteroscedastic errors," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 70-93.
- Lai, Peng & Li, Gaorong & Lian, Heng, 2013. "Quadratic inference functions for partially linear single-index models with longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 118(C), pages 115-127.
- Guo-Liang Fan & Han-Ying Liang & Jiang-Feng Wang, 2013. "Empirical likelihood for heteroscedastic partially linear errors-in-variables model with α-mixing errors," Statistical Papers, Springer, vol. 54(1), pages 85-112, February.
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