Statistical inference of partially linear regression models with heteroscedastic errors
نویسندگان
چکیده
منابع مشابه
Bias-corrected statistical inference for partially linear varying coefficient errors-in-variables models with restricted condition
In this paper, we consider the statistical inference for the partially liner varying coefficient model with measurement error in the nonparametric part when some prior information about the parametric part is available. The prior information is expressed in the form of exact linear restrictions. Two types of local bias-corrected restricted profile least squares estimators of the parametric comp...
متن کاملEmpirical likelihood for heteroscedastic partially linear models
AMS 2000 subject classifications: 62F35 62G20 Keywords: Double robustness Empirical likelihood Heteroscedasticity Kernel estimation Partially linear model Semiparametric efficiency a b s t r a c t We make empirical-likelihood-based inference for the parameters in heteroscedastic partially linear models. Unlike the existing empirical likelihood procedures for heteroscedastic partially linear mod...
متن کاملAsymptotic Inference in Some Heteroscedastic Regression Models with Long Memory Design and Errors
This paper discusses asymptotic distributions of various estimators of the underlying parameters in some regression models with long memory (LM) Gaussian design and nonparametric heteroscedastic LM moving average errors. In the simple linear regression model, the first-order asymptotic distribution of the least square estimator of the slope parameter is observed to be degenerate. However, in th...
متن کاملInference for linear models with dependent errors
The paper is concerned with inference for linear models with fixed regressors and weakly dependent stationary time series errors. Theoretically, we obtain asymptotic normality for the M -estimator of the regression parameter under mild conditions and establish a uniform Bahadur representation for recursive M -estimators. Methodologically, we extend the recently proposed self-normalized approach...
متن کاملStatistical Inference for Semiparametric Varying-coefficient Partially Linear Models with Error-prone Linear Covariates
We study semiparametric varying-coefficient partially linear models when some linear covariates are not observed, but ancillary variables are available. Semiparametric profile least-square based estimation procedures are developed for parametric and nonparametric components after we calibrate the error-prone covariates. Asymptotic properties of the proposed estimators are established. We also p...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Multivariate Analysis
سال: 2007
ISSN: 0047-259X
DOI: 10.1016/j.jmva.2007.06.011