CLT of wavelet estimator in semiparametric model with correlated errors

This paper considers the semiparametric regression model y (i) = x (i) beta+g(t (i) )+V (i) (1 a parts per thousand currency sign i a parts per thousand currency sign n), where (x (i) , t (i) ) are known design points, beta is an unknown slope parameter, g(center dot) is an unknown function, the correlated errors with , and e (i) are negatively associated random variables. Under appropriate conditions, the authors study the asymptotic normality for wavelet estimators of beta and g(center dot). A simulation study is undertaken to investigate finite sample behavior of the estimators.