Berry-Esseen bound of wavelet estimators in heteroscedastic regression model with random errors

For the heteroscedastic regression model Y-i = x(i)beta + g(t(i)) + sigma(i)e(i), 1 <= i <= n, where sigma(2)(i) = f (u(i)), (x(i), t(i), u(i)) are known to be nonrandom design points, g(.) and f (.) are defined on the closed interval [0,1]. When f (.) is known, we investigate the Berry-Esseen type bounds for wavelet estimators of beta and g(.) under {e(i)} are identically distributed phi-mixing random errors, when f (.) is unknown, the Berry-Esseen type bounds for wavelet estimators of beta,g(.) and f(.) established under {e(i)} are independent random errors.