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Testing goodness-of-fit of parametric spatial Trends
(M D P I AG, 2018-09-17)
[Abstract] The aim of this work is to propose and analyze the behavior of a test statistic to assess a parametric trend surface, that is, a regression model with spatially correlated errors. The asymptotic behavior under ...
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 ...
Nonparametric Regression Estimation for Circular Data
(M D P I AG, 2019-07-31)
[Abstract] Non-parametric regression with a circular response variable and a unidimensional linear regressor is a topic which was discussed in the literature. In this work, we extend the results to the case of multivariate ...
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 estimation for a functional-circular regression model
(Springer, 2024)
[Abstract]: Changes on temperature patterns, on a local scale, are perceived by individuals as the most direct indicators of global warming and climate change. As a specific example, for an Atlantic climate location, spring ...
Nonparametric Conditional Risk Mapping Under Heteroscedasticity
(Springer Nature, 2024-03)
[Absctract]: A nonparametric procedure to estimate the conditional probability that a nonstationary geostatistical process exceeds a certain threshold value is proposed. The method consists of a bootstrap algorithm that ...