'i, X'j )' ; using the sampled data we seek to construct a nonparametric estimate of the mean regression function g … regression function at (i) a point and (ii) under the infinity norm. Second, we calculate (i) pointwise and (ii) uniform … convergence rates for the dyadic analog of the familiar Nadaraya-Watson (NW) kernel regression estimator. We show that the NW …

able to impose monotonicity of the estimated function. The use of such a shape restriction may signi cantly improve the … constrained estimator that imposes the monotonicity, on the other hand, signi cantly reduces variance by removing oscillations of …

We consider a difference based ridge regression estimator and a Liu type estimator of the regression parameters in the … partial linear semiparametric regression model, y = Xβ + f + Both estimators are analysed and compared in the sense of mean … ; Differencing matrix ; Liu estimator ; Liu type estimator ; Multicollinearity ; Ridge regression estimator ; Semiparametric model …

In this paper uniform confidence bands are constructed for nonparametric quantile estimates of regression functions … respect to different education levels. -- Bootstrap ; Quantile Regression ; Confidence Bands ; Nonparametric Fitting ; Kernel …

-- Optimal rate of convergence ; nonparametric regression ; long memory ; antipersistence …