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Nonparametric estimation of the conditional variance function with correlated errors
(Taylor & Francis, 2006)
Local polynomial regression estimation with correlated errors
(Taylor & Francis, 2001)
In this paper, we study the nonparametric estimation of the regression
function and its derivatives using weighted local polynomial fitting. Consider
the fixed regression model and suppose that the random observation ...
On the uniform strong consistency of local polynomial regression under dependence conditions
(Taylor & Francis, 2003)
[Abstract] In this paper, nonparametric estimators of the regression function, and its derivatives, obtained by means of weighted local polynomial fitting are studied. Consider the fixed regression model where the error ...
Local polynomial regression smoothers with AR-error structure
(Springer, 2002)
Consider the fixed regression model with random observation error that follows an
AR(1) correlation structure. In this paper, we study the nonparametric estimation
of the regression function and its derivatives using a ...
Weighted Local Nonparametric Regression with Dependent Errors: Study of Real Private Residential Fixed Investment in the USA
(Kluwer Academic Publishers, 2004)
This paper presents an overview of the existing literature on the nonparametric local
polynomial (LPR) estimator of the regression function and its derivatives when the observations are
dependent. When the errors of the ...
Analysis of interval‐grouped data in weed science: The binnednp Rcpp package
(John Wiley & Sons Ltd., 2019-09-13)
[Abstract] Weed scientists are usually interested in the study of the distribution and density functions of the random variable that relates weed emergence with environmental indices like the hydrothermal time (HTT). ...
Nonparametric multiple regression estimation for circular response
(2021)
Nonparametric estimators of a regression function with circular response and -valued predictor are considered in this work. Local polynomial estimators are proposed and studied. Expressions for the asymptotic conditional ...
A goodness-of-fit test for regression models with spatially correlated errors
(2020)
The problem of assessing a parametric regression model in the presence of spatial correlation is addressed in this work. For that purpose, a goodness-of-fit test based on a -distance comparing a parametric and nonparametric ...
Bagging cross-validated bandwidths with application to big data
(2021)
Hall & Robinson (2009) proposed and analysed the use of bagged cross-validation to choose the band-width of a kernel density estimator. They established that bagging greatly reduces the noise inherent in ordinary ...
Nonparametric geostatistical risk mapping
(2018)
In this work, a fully nonparametric geostatistical approach to estimate threshold exceeding probabilities is proposed. To estimate the large-scale variability (spatial trend) of the process, the nonparametric local linear ...