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Fast Kernel Smoothing in R with Applications to Projection Pursuit [PDF]
Journal of Statistical Software, 2022 This paper introduces the R package FKSUM, which offers fast and exact evaluation of univariate kernel smoothers. The main kernel computations are implemented in C++, and are wrapped in simple, intuitive and versatile R functions.
David P. Hofmeyr
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Integral approximation by kernel smoothing [PDF]
Bernoulli, 2014 Let $(X_1,\ldots,X_n)$ be an i.i.d. sequence of random variables in $\mathbb{R}^d$, $d\geq 1$. We show that, for any function $\varphi :\mathbb{R}^d\rightarrow\mathbb{R}$, under regularity conditions, \[n^ {1/2}\Biggl(n^{-1}\sum_{i=1}^n\frac{\varphi(X_i)}
B. Delyon, Franccois Portier
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Discrete Heat Kernel Smoothing in Irregular Image Domains. [PDF]
Annu Int Conf IEEE Eng Med Biol Soc, 2018 We present the discrete version of heat kernel smoothing on graph data structure. The method is used to smooth data in an irregularly shaped domains in 3D images. New statistical properties of heat kernel smoothing are derived. As an application, we show
Chung MK, Wang Y, Wu G.
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Smooth ECE: Principled Reliability Diagrams via Kernel Smoothing [PDF]
International Conference on Learning Representations, 2023 Calibration measures and reliability diagrams are two fundamental tools for measuring and interpreting the calibration of probabilistic predictors.
Jaroslaw Blasiok, Preetum Nakkiran
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Multivariate Kernel Smoothing and Its Applications [PDF]
Journal of the American Statistical Association, 2020 Multivariate Kernel Smoothing and Its Applications, by J.E. Chacón and T. Duong, provides a comprehensive and up-todate introduction of multivariate density estimation.
Qing Wang
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Kernel smoothing dos dados de chuva no Nordeste [PDF]
Revista Brasileira de Engenharia Agrícola e Ambiental, 2014 O regime de chuvas sobre o Nordeste do Brasil é bastante complexo, sendo considerado sazonal, além de sofrer fortes influências dos fenômenos El Niño, La Niña e outros sistemas meteorológicos, como o dipolo, atuantes sobre as bacias do oceano Atlântico ...
Nyedja F. M. Barbosa +5 more
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Kernel Estimation: the Equivalent Spline Smoothing Method [PDF]
SSRN Electronic Journal, 1994 Summary: Among nonparametric smoothers, there is a well-known correspondence between kernel and Fourier series methods, pivoted by the Fourier transform of the kernel. This suggests a similar relationship between kernel and spline estimators. A known special case is the result of \textit{B. W. Silverman} [Ann. Stat.
Wolfgang Karl Härdle, Michael Nussbaum
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Journal of Physics: Conference Series, 2018 The functions which describe relationship of more than one response variables observed at several values of the predictor variables in which there are correlations among the responses can be estimated by using a multi-response nonparametric regression ...
Budi Lestari +3 more
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Smoothing parameter selection method for multiresponse nonparametric regression model using smoothing spline and Kernel estimators approaches [PDF]
Journal of Physics: Conference Series, 2019 The principle problem in multiresponse nonparametric regression model is how we estimate the regression functions which draw association between some dependent (response) variables and some independent (predictor) variables where there are correlations ...
Budi Lestari +3 more
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Estimating Yield Curves by Kernel Smoothing Methods [PDF]
, 2016 We introduce a new method for the estimation of discount functions, yield curves and forward curves from government issued coupon bonds. Our approachis nonparametric and does not assume a particular functional form for thediscount function although we do show how to impose various restrictions inthe estimation.
Oliver Linton +3 more
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