Estimation of Regression Model Using a Two Stage Nonparametric Approach

Estimation of Regression Model Using a Two Stage Nonparametric Approach

Based on the empirical or theoretical qualitative information about the relationship between response variable and covariates, we propose a new approach to model polynomial regression using a shape restricted regression after estimating the direction by sufficient dimension reduction. The purpose of this paper is to illustrate that in the absence of prior information other than the shape constr...

Nonparametric Survey Regression Estimation in Two-Stage Spatial Sampling

A nonparametric model-assisted survey estimator for status estimation based on local polynomial regression is extended to incorporate spatial auxiliary information. Under mild assumptions, this estimator is design-unbiased and consistent. Simulation studies show that the nonparametric regression estimator is competitive with standard parametric techniques when a parametric specification is corr...

Nonparametric Regression Estimation under Kernel Polynomial Model for Unstructured Data

The nonparametric estimation(NE) of kernel polynomial regression (KPR) model is a powerful tool to visually depict the effect of covariates on response variable, when there exist unstructured and heterogeneous data. In this paper we introduce KPR model that is the mixture of nonparametric regression models with bootstrap algorithm, which is considered in a heterogeneous and unstructured framewo...

THE COMPARISON OF TWO METHOD NONPARAMETRIC APPROACH ON SMALL AREA ESTIMATION (CASE: APPROACH WITH KERNEL METHODS AND LOCAL POLYNOMIAL REGRESSION)

Small Area estimation is a technique used to estimate parameters of subpopulations with small sample sizes.  Small area estimation is needed  in obtaining information on a small area, such as sub-district or village.  Generally, in some cases, small area estimation uses parametric modeling.  But in fact, a lot of models have no linear relationship between the small area average and the covariat...

Nonparametric estimation of a switching regression model