Oracally Efficient Two-Step Estimation of Generalized Additive Model

Oracally Efficient Two-Step Estimation of Generalized Additive Model

Oracally Efficient Two-Step Estimation of Generalized Additive Model Rong Liu a b , Lijian Yang a c & Wolfgang K. Härdle d a Center for Advanced Statistics and Econometrics Research , Soochow University , China b Department of Mathematics and Statistics , University of Toledo , Toledo , OH , 43606 c Department of Statistics and Probability , Michigan State University , East Lansing , MI , 48824...

Oracally efficient two-step estimation for additive regression

Model-assisted Estimation of Forest Resources with Generalized Additive Models

Multi-phase surveys are often conducted in forest inventory, with the goal of estimating forested area and tree characteristics over large regions. This article describes how design-based estimation of such quantities, based on information gathered during ground visits of sampled plots, can be made more precise by incorporating auxiliary information available from remote sensing. The relationsh...

Oracally efficient spline smoothing of nonlinear additive autoregression models with simultaneous confidence band

Under weak conditions of smoothness and mixing, we propose splinebackfitted spline (SBS) estimators of the component functions for nonlinear additive autoregression model. The proposed SBS estimator is both computationally expedient for analyzing high dimensional large time series data since it can circumvent the curse of dimensionality, and theoretically reliable as the estimator is oracally e...

Polynomial Spline Estimation for A Generalized Additive Coefficient Model.

We study a semiparametric generalized additive coefficient model, in which linear predictors in the conventional generalized linear models is generalized to unknown functions depending on certain covariates, and approximate the nonparametric functions by using polynomial spline. The asymptotic expansion with optimal rates of convergence for the estimators of the nonparametric part is establishe...