Add to ORKGFan and Gijbels conjectured that the local polynomial estimator achieve the minimax risk at the boundary point. This paper proves their conjecture that the local polynomial regression smoothers achieve the linear minimax efficiency at the boundary point over an ideal class of functions
Motivated by the advantages the local linear fitting method provides for estimation of den-sities ne...
The local multi-resolution projection estimator (LMPE) has been first introduced in [7]. It was prov...
There has been much justifiable recent interest in local polynomial regression, and in particular in...
This paper proves that local polynomial regression smoothers achieve linear minimax efficiency over ...
We consider local polynomial fitting for estimating a regression function and its derivatives nonpar...
We consider local polynomial fitting for estimating a regression function and its derivatives nonpar...
Suppose we have a number of noisy measurements of an unknown real-valued function f near a point of ...
SUMMARY. Local polynomial smoothers recently received much attention in the lit-erature, owing to th...
The asymptotic bias and variance of a general class of local polynomial estimators of M-regression f...
Local polynomial methods hold considerable promise for boundary estimation, where they offer unmatch...
Under a standard assumption in complexity theory (NP ̸ ⊂ P/poly), we demonstrate a gap between the m...
summary:Local polynomials are used to construct estimators for the value $m(x_{0})$ of the regressio...
The paper focuses on the adaptation of local polynomial filters at the end of the sample period. We...
We investigate the extension of binning methodology to fast computation of several auxiliary quantit...
We consider the problem of the nonparametric minimax estimation of a multivariate density at a given...
Motivated by the advantages the local linear fitting method provides for estimation of den-sities ne...
The local multi-resolution projection estimator (LMPE) has been first introduced in [7]. It was prov...
There has been much justifiable recent interest in local polynomial regression, and in particular in...
This paper proves that local polynomial regression smoothers achieve linear minimax efficiency over ...
We consider local polynomial fitting for estimating a regression function and its derivatives nonpar...
We consider local polynomial fitting for estimating a regression function and its derivatives nonpar...
Suppose we have a number of noisy measurements of an unknown real-valued function f near a point of ...
SUMMARY. Local polynomial smoothers recently received much attention in the lit-erature, owing to th...
The asymptotic bias and variance of a general class of local polynomial estimators of M-regression f...
Local polynomial methods hold considerable promise for boundary estimation, where they offer unmatch...
Under a standard assumption in complexity theory (NP ̸ ⊂ P/poly), we demonstrate a gap between the m...
summary:Local polynomials are used to construct estimators for the value $m(x_{0})$ of the regressio...
The paper focuses on the adaptation of local polynomial filters at the end of the sample period. We...
We investigate the extension of binning methodology to fast computation of several auxiliary quantit...
We consider the problem of the nonparametric minimax estimation of a multivariate density at a given...
Motivated by the advantages the local linear fitting method provides for estimation of den-sities ne...
The local multi-resolution projection estimator (LMPE) has been first introduced in [7]. It was prov...
There has been much justifiable recent interest in local polynomial regression, and in particular in...