Functional Estimation for Density, Regression Models and Processes PDF

Functional Estimation For Density, Regression Models And ...

Contents: Introduction Kernel Estimator of a Density Kernel Estimator of a Regression Function Limits for the Varying Bandwidths Estimators Nonparametric Estimation of Quantiles Nonparametric Estimation of Intensities for Stochastic Processes Estimation in Semi-Parametric Regression Models Diffusion Processes Applications to Time Series

Functional Estimation for Density, Regression Models and ...

Fig. 3 (left panel) shows the estimated functional regression coefficients for groups 1 (solid lines) and 10 (dashed lines). The intercepts γ 0 1 and γ 0 10 (black lines) are effectively zero except for upward ticks near the boundaries. In effect, the regression model is both identifying and attempting to correct for the boundary-bias in the density estimates.