regression model. Asymptotic distribution theory is developed for the estimation method which enjoys the same rate of convergence …

We consider the problem of estimating quantile regression coefficients in errors-in-variables models. When the error … unknown, the regression quantile estimates based on orthogonal residuals are shown to be consistent and asymptotically normal …. -- semiparametric model ; Kernel ; linear regression ; errors-in-variables ; regression quantile …

Optimal bandwidths for local polynomial regression usually involve functionals of the derivatives of the unknown … regression function. In the multivariate case, estimates of these functionals are not readily available, primarily because … local quadratic regression with cross terms left out. This estimator has the optimal rate of convergence but is simpler and …

for the production function is discussed. -- Nonparametric Regression ; Additive Models ; Testing Additivity ; Derivative …

This methodological paper discusses the application of "adaptive" non-parametric procedures for estimating regression …