TY - JOUR
T1 - Strong convergence rates of several estimators in semiparametric varying-coefficient partially linear models
AU - Zhou, Yong
AU - You, Jinhong
AU - Wang, Xiaojing
PY - 2009/9
Y1 - 2009/9
N2 - This article is concerned with the estimating problem of semiparametric varying-coefficient partially linear regression models. By combining the local polynomial and least squares procedures Fan and Huang (2005) proposed a profile least squares estimator for the parametric component and established its asymptotic normality. We further show that the profile least squares estimator can achieve the law of iterated logarithm. Moreover, we study the estimators of the functions characterizing the non-linear part as well as the error variance. The strong convergence rate and the law of iterated logarithm are derived for them, respectively.
AB - This article is concerned with the estimating problem of semiparametric varying-coefficient partially linear regression models. By combining the local polynomial and least squares procedures Fan and Huang (2005) proposed a profile least squares estimator for the parametric component and established its asymptotic normality. We further show that the profile least squares estimator can achieve the law of iterated logarithm. Moreover, we study the estimators of the functions characterizing the non-linear part as well as the error variance. The strong convergence rate and the law of iterated logarithm are derived for them, respectively.
KW - 62G05
KW - 62G20
KW - error variance
KW - law of iterated logarithm
KW - partially linear regression model
KW - profile leastsquares
KW - strong convergence rate
KW - varying-coefficient
UR - https://www.scopus.com/pages/publications/67949083709
U2 - 10.1016/S0252-9602(09)60090-4
DO - 10.1016/S0252-9602(09)60090-4
M3 - 文章
AN - SCOPUS:67949083709
SN - 0252-9602
VL - 29
SP - 1113
EP - 1127
JO - Acta Mathematica Scientia
JF - Acta Mathematica Scientia
IS - 5
ER -