Nonparametric additive model-assisted estimation for survey data
نویسندگان
چکیده
منابع مشابه
Nonparametric additive model-assisted estimation for survey data
An additive model-assisted nonparametric method is investigated to estimate the finite population totals of massive survey data with the aid of auxiliary information. A class of estimators is proposed to improve the precision of the well known Horvitz-Thompson estimators by combining the spline and local polynomial smoothing methods. These estimators are calibrated, asymptotically design-unbias...
متن کاملNonparametric 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...
متن کاملNonparametric Estimation of an Additive Quantile Regression Model
This paper is concerned with estimating the additive components of a nonparametric additive quantile regression model. We develop an estimator that is asymptotically normally distributed with a rate of convergence in probability of n−r/(2r+1) when the additive components are r-times continuously differentiable for some r ≥ 2. This result holds regardless of the dimension of the covariates and, ...
متن کاملNonparametric estimation of an additive model with a link function
This paper describes an estimator of the additive components of a nonparametric additive model with a known link function. When the additive components are twice continuously differentiable, the estimator is asymptotically normally distributed with a rate of convergence in probability of 2 / 5 n− . This is true regardless of the (finite) dimension of the explanatory variable. Thus, in contrast ...
متن کاملNonparametric estimation for dependent data
Nonparametric estimation for dependent observations has a long history in statistics. Rosenblatt [42] first studied density estimation for dependent data. Since then several authors have considered nonparametric estimation under various assumptions (notable early articles include Robinson [39] and Hart [29]). For example, Hall and Hart [25], Giraitis et al. [22], Mielniczuk [34] and Estevas and...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Multivariate Analysis
سال: 2011
ISSN: 0047-259X
DOI: 10.1016/j.jmva.2011.03.006