This paper considers the semiparametric regression model Yi = xiβ＋g（ti）＋ Vi （1 ≤ i≤ n）, where （xi, ti） are known design points, fl is an unknown slope parameter, g（.） is an unknown function, the correlate...This paper considers the semiparametric regression model Yi = xiβ＋g（ti）＋ Vi （1 ≤ i≤ n）, where （xi, ti） are known design points, fl is an unknown slope parameter, g（.） is an unknown function, the correlated errors Vi = ∑^∞j=-∞cjei-j with ∑^∞j=-∞｜cj｜ 〈 ∞, and ei are negatively associated random variables. Under appropriate conditions, the authors study the asymptotic normality for wavelet estimators ofβ and g（·）. A simulation study is undertaken to investigate finite sample behavior of the estimators.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.10871146
文摘This paper considers the semiparametric regression model Yi = xiβ＋g（ti）＋ Vi （1 ≤ i≤ n）, where （xi, ti） are known design points, fl is an unknown slope parameter, g（.） is an unknown function, the correlated errors Vi = ∑^∞j=-∞cjei-j with ∑^∞j=-∞｜cj｜ 〈 ∞, and ei are negatively associated random variables. Under appropriate conditions, the authors study the asymptotic normality for wavelet estimators ofβ and g（·）. A simulation study is undertaken to investigate finite sample behavior of the estimators.
