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Statistical inference of partially linear regression models with heteroscedastic errors
- Source :
- Journal of Multivariate Analysis. 98(8):1539-1557
- Publication Year :
- 2007
- Publisher :
- Elsevier BV, 2007.
-
Abstract
- 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.
- Subjects :
- Statistics and Probability
Heteroscedasticity
Statistics::Theory
Numerical Analysis
Statistics::Applications
Nonparametric statistics
Linear model
Model selection
Local polynomial
Semiparametric model
Goodness of fit
Statistics
Econometrics
Asymptotic normality
Statistics::Methodology
Semiparametric regression
Semiparametric regression model
Statistics, Probability and Uncertainty
Park test
Variance function
Mathematics
Subjects
Details
- ISSN :
- 0047259X
- Volume :
- 98
- Issue :
- 8
- Database :
- OpenAIRE
- Journal :
- Journal of Multivariate Analysis
- Accession number :
- edsair.doi.dedup.....0bc3011aaac678113ca83889a483a84f
- Full Text :
- https://doi.org/10.1016/j.jmva.2007.06.011