602 Citations
Bias Correction Estimation for a Continuous‐Time Asset Return Model with Jumps
- MathematicsJournal of Time Series Analysis
- 2018
In this article, local linear estimators are adapted for the unknown infinitesimal coefficients associated with continuous‐time asset return models with jumps, which can correct the bias…
Direct Semi�?Parametric Estimation of Fixed Effects Panel Data Varying Coefficient Models
- Mathematics, Computer Science
- 2014
A one‐step backfitting algorithm is proposed that enables the resulting estimator to achieve optimal rates of convergence for this type of problem and exhibits the so‐called oracle efficiency property.
QUANTILE REGRESSION FOR CLIMATE DATA
- Mathematics
- 2014
Quantile regression is a developing statistical tool which is used to explain the relationship between response and predictor variables. This thesis describes two examples of climatology using…
A New Version of Local Linear Estimators
- Mathematics
- 2013
In the current article we proposed a new version of local linear estimators.The main idea here is to combine two estimators to produce a new estimator having the best features from the original…
Literature Review for Local Polynomial Regression
- Mathematics
- 2010
This paper discusses key results from the literature in the field of local polynomial regression. Local polynomial regression (LPR) is a nonparametric technique for smoothing scatter plots and…
An evaluation of non-parametric relative risk estimators for disease maps
- Computer ScienceComput. Stat. Data Anal.
- 2004
LOCAL FITTING WITH A POWER BASIS
- Mathematics
- 2004
• Local polynomial modelling can be seen as a local fit of the data against a polynomial basis. In this paper we extend this method to the power basis, i.e. a basis which consists of the powers of an…
Variable bandwidth and one-step local M-estimator
- Mathematics
- 2000
A robust version of local linear regression smoothers augmented with variable bandwidth is studied. The proposed method inherits the advantages of local polynomial regression and overcomes the…
Understanding exponential smoothing via kernel regression
- Mathematics, Computer Science
- 1999
This paper shows that exponential smoothing can be put into a nonparametric regression framework and gains some interesting insights into its performance through this interpretation, and uses theoretical developments from the kernel regression field to derive, for the first time, asymptotic properties of exponential smoothed forecasters.
Bandwidth selection for statistical matching and prediction
- Economics
- 2021
Funding information MINECO grant MTM2017-82724-R, Xunta de Galicia (Grupos de Referencia Competitiva ED431C-2020-14 and Centro de Investigación del Sistema Universitario de Galicia ED431G 2019/01),…
References
SHOWING 1-10 OF 19 REFERENCES
Design-adaptive Nonparametric Regression
- Mathematics
- 1992
Abstract In this article we study the method of nonparametric regression based on a weighted local linear regression. This method has advantages over other popular kernel methods. Moreover, such a…
On the bias of variable bandwidth curve estimators
- Mathematics
- 1990
SUMMARY A major difficulty in understanding the properties of variable bandwidth methods (Breiman, Meisel & Purcell, 1977; Abramson, 1982) is that extremely lengthy and complex algebra is needed to…
Variable kernel density estimates and variable kernel density estimates
- Computer Science
- 1990
The importance of the distinction between these two definitions of kernel density estimate is stressed, both via an introductory description of the ideas involved and in terms of their comparative theoretical performance.
A Unifying Approach to Nonparametric Regression Estimation
- Mathematics, Computer Science
- 1988
A class of kernel estimators with local bandwidth depending on the density of the design points is introduced, where the degree of design adaptation may be expressed by a single parameter α in [0, 1].
Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting
- Mathematics
- 1988
Abstract Locally weighted regression, or loess, is a way of estimating a regression surface through a multivariate smoothing procedure, fitting a function of the independent variables locally and in…
Variable window width kernel estimates of probability densities
- Computer Science
- 1988
Modifications of estimators proposed by Breiman, Meisel and Purcell and Abramson, which have variable window widths, are seen to have very fast rates of convergence.
Variable Bandwidth Kernel Estimators of Regression Curves
- Mathematics
- 1987
On montre qu'en termes de l'erreur en moyenne quadratique integree asymptotique, les estimateurs du noyau avec un certain choix de largeur de bande local sont superieurs aux estimateurs ordinaires du…
Weighted Local Regression and Kernel Methods for Nonparametric Curve Fitting
- Mathematics, Computer Science
- 1987
It is proved that in the fixed design regression model, given a weighted local regression procedure with any weight function, there is a corresponding kernel method such that the quotients of weights distributed by both methods tend uniformly to 1 as the number of observations increases to infinity.
Density estimation for statistics and data analysis
- Computer Science
- 1986
The Kernel Method for Multivariate Data: Three Important Methods and Density Estimation in Action.