More Ef cient Local Polynomial Estimation in Nonparametric Regression With Autocorrelated Errors

Local polynomial estimation in partial linear regression models under dependence

A regression model whose regression function is the sum of a linear and a nonparametric component is presented. The design is random and the response and explanatory variables satisfy mixing conditions. A new local polynomial type estimator for the nonparametric component of the model is proposed and its asymptotic normality is obtained. Specifically, this estimator works on a prewhitening tran...

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...

Local Polynomial Fitting with Long-memory, Short-memory and Antipersistent Errors

Nonparametric regression with long-range, short-range and antipersistent errors is considered. Local polynomial smoothing is investigated for the estimation of the trend function and its derivatives. It is well known that in the presence of long memory (with a fractional di erencing parameter 0 < d < 1=2), nonparametric regression estimators converge at a slower rate than in the case of uncorre...

Efficient Kernel Estimation in Nonparametric Regression with Autocorrelated Errors

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...