Unified heat kernel regression for diffusion, kernel smoothing and wavelets on manifolds and its application to mandible growth modeling in CT images. [PDF]
Med Image Anal, 2015 We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a ...
Chung MK, Qiu A, Seo S, Vorperian HK.
europepmc +6 more sources
ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R [PDF]
Journal of Statistical Software, 2007 Kernel smoothing is one of the most widely used non-parametric data smoothing techniques. We introduce a new R package ks for multivariate kernel smoothing.
Tarn Duong
doaj +1 more source
On kernel smoothing for extremal quantile regression [PDF]
, 2012 Nonparametric regression quantiles obtained by inverting a kernel estimator of the conditional distribution of the response are long established in statistics.
A. Daouia, L. Gardes, S. Girard
semanticscholar +10 more sources
KVLMM: A Trajectory Prediction Method Based on a Variable-Order Markov Model With Kernel Smoothing
IEEE Access, 2018 With the dramatic proliferation of global positioning system (GPS) devices, a rich range of research has been conducted on the analysis of GPS trajectories.
Xing Wang +3 more
doaj +2 more sources
Kernel smoothing in partial linear models
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1988 SUMMARY Kernel smoothing is studied in partial linear models, i.e. semiparametric models of the form yi=ξi′β+f(ti)+εi(1⩽i⩽n), where the ξi are fixed known p vectors, β is an unknown vector parameter and f is a smooth but unknown function.
P. Speckman
semanticscholar +3 more sources
A Comparative Study of Boundary Effects for Kernel Smoothing
Austrian Journal of Statistics, 2016 The problem of boundary effects for nonparametric kernel regression is considered. We will follow the problem of bandwidth selection for Gasser-Müller estimator especially.
Jan Koláček, Jitka Poměnková
doaj +2 more sources
Yield Curve Estimation by Kernel Smoothing Methods [PDF]
SSRN Electronic Journal, 2000 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Linton, O. +3 more
core +11 more sources
Heat kernel smoothing using Laplace-Beltrami eigenfunctions. [PDF]
Med Image Comput Comput Assist Interv, 2010 We present a novel surface smoothing framework using the Laplace-Beltrami eigenfunctions. The Green's function of an isotropic diffusion equation on a manifold is constructed as a linear combination of the Laplace-Beltraimi operator. The Green's function is then used in constructing heat kernel smoothing.
Seo S, Chung MK, Vorperian HK.
europepmc +4 more sources
Examining Potential Boundary Bias Effects in Kernel Smoothing on Equating: An Introduction for the Adaptive and Epanechnikov Kernels. [PDF]
Appl Psychol Meas, 2015 Cid JA, von Davier AA.
europepmc +2 more sources
Estimating Mixture of Gaussian Processes by Kernel Smoothing. [PDF]
J Bus Econ Stat, 2014 Huang M, Li R, Wang H, Yao W.
europepmc +2 more sources