Michael G. Akritas, On the Use of Nonparametric Regression Techniques for Fitting Parametric Regression Models, Biometrics, Vol. 52, No. 4 (Dec., 1996), pp. 1342-1362 ...

We propose two new consistent estimators for the parametric regression, which address the endogeneity in the regressor by means of spatial bounding and bias correction using non-parametric estimation.

Recent advances in nonparametric regression for functional data have focused on enhancing estimator performance whilst addressing practical issues such as bandwidth selection and model adaptivity.

In case we know the relationship between the response and part of explanatory variables and do not know the relationship between the response and the other part of explanatory variables we use ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Nonparametric Regression for Functional Data Publication Trend The graph below shows the total number of publications each year in Nonparametric Regression for Functional Data.