Asymptotic properties of a semiparametric regression estimator proposed in Glad (1996) are derived, without conditioning on the predictor variables. The leading terms of unconditional asymptotic bias and variance are equal to those in the expressions obtained conditioned on the design in Glad (1996), while the unconditional approximations derived in this paper are of higher accuracy.Bias reduction Correction factor Kernel estimators Nadaraya-Watson estimator Semiparametric regression Unconditional properties
Nonparametric kernel estimators are mostly used in a variety of statistical research fields. Nadaray...
The purpose of this study is to determine the effect of three improvement methods on nonparametric k...
Regression analysis is one of statistical analysis usually used to investigate the pattern of functi...
The purpose of this study is to determine the effect of three improvement methods on nonparametric k...
Abstract. We investigate the asymptotic behavior of the Nadaraya-Watson esti-mator for the estimatio...
We investigate the asymptotic behavior of the Nadaraya-Watson estimator for the estimation of the re...
We investigate the asymptotic behavior of the Nadaraya-Watson estimator for the estimation of the re...
dth: 0px; "> Given a data set (xi , yi ) and connecting between xi and yi be assumed to follownon...
AbstractNonparametric kernel regression estimators of the Nadaraya-Watson type are known to have an ...
AbstractNonparametric kernel regression estimators of the Nadaraya-Watson type are known to have an ...
International audienceWe study the problem of semiparametric estimation of a multivariate count regr...
It has been shown in recent years that quotient (Nadaraya-Watson) and convolution (Priestley-Chao or...
International audienceWe study the problem of semiparametric estimation of a multivariate count regr...
This article compared the performance between finite order kernel (normal) and infinite order kernel...
The Nadaraya-Watson estimator is certainly the most popular nonparametric regression estimator. The ...
Nonparametric kernel estimators are mostly used in a variety of statistical research fields. Nadaray...
The purpose of this study is to determine the effect of three improvement methods on nonparametric k...
Regression analysis is one of statistical analysis usually used to investigate the pattern of functi...
The purpose of this study is to determine the effect of three improvement methods on nonparametric k...
Abstract. We investigate the asymptotic behavior of the Nadaraya-Watson esti-mator for the estimatio...
We investigate the asymptotic behavior of the Nadaraya-Watson estimator for the estimation of the re...
We investigate the asymptotic behavior of the Nadaraya-Watson estimator for the estimation of the re...
dth: 0px; "> Given a data set (xi , yi ) and connecting between xi and yi be assumed to follownon...
AbstractNonparametric kernel regression estimators of the Nadaraya-Watson type are known to have an ...
AbstractNonparametric kernel regression estimators of the Nadaraya-Watson type are known to have an ...
International audienceWe study the problem of semiparametric estimation of a multivariate count regr...
It has been shown in recent years that quotient (Nadaraya-Watson) and convolution (Priestley-Chao or...
International audienceWe study the problem of semiparametric estimation of a multivariate count regr...
This article compared the performance between finite order kernel (normal) and infinite order kernel...
The Nadaraya-Watson estimator is certainly the most popular nonparametric regression estimator. The ...
Nonparametric kernel estimators are mostly used in a variety of statistical research fields. Nadaray...
The purpose of this study is to determine the effect of three improvement methods on nonparametric k...
Regression analysis is one of statistical analysis usually used to investigate the pattern of functi...