The Priestley-Chao Estimator of Conditional Density with Uniformly Distributed Random Design [PDF]
The present paper is focused on non-parametric estimation of conditional density. Conditional density can be regarded as a generalization of regression thus the kernel estimator of conditional density can be derived from the kernel estimator of the ...
Kateřina Konečná
doaj
Best Possible Constant for Bandwidth Selection
For the data based choice of the bandwidth of a kernel density estimator, several methods have recently been proposed which have a very fast asymptotic rate of convergence to the optimal bandwidth. In particular the relative rate of convergence is the square root of the sample size, which is known to be the best possible.
Fan, Jianqing, Marron, James S.
openaire +3 more sources
Bandwidth Selection Problem in Nonparametric Functional Regression [PDF]
The focus of this paper is the nonparametric regression where the predictor is a functional random variable, and the response is a scalar. Functional kernel regression belongs to popular nonparametric methods used for this purpose. The two key problems
Daniela Kuruczová, Jan Koláček
doaj
Optimal Bandwidth Selection for Kernel Density Functionals Estimation
The choice of bandwidth is crucial to the kernel density estimation (KDE) and kernel based regression. Various bandwidth selection methods for KDE and local least square regression have been developed in the past decade.
Su Chen
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An R Package Implementation for Statistical Modeling of Emergence Curves in Weed Science
Over the last few years, the research group MODES has carried out a research line (in collaboration with researchers from the Sustainable Agriculture Institute of the CSIC in Córdoba) on statistical modeling in weed science. One of the aspects dealt with
Daniel Barreiro-Ures +2 more
doaj +1 more source
Bandwidth selection for kernel conditional density estimation [PDF]
We consider bandwidth selection for kernel estimators of conditional densities with one explanatory variable. Several bandwidth selection methods are derived, ranging from fast rules-of-thumb which assume the underlying densities are known to relatively slow procedures which use the bootstrap.
Bashtannyk, D. M., Hyndman, R. J.
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Optimal Bandwidth Selection in Heteroskedasticity–Autocorrelation Robust Testing [PDF]
The paper considers studentized tests in time series regressions with nonparametrically autocorrelated errors. The studentization is based on robust standard errors with truncation lag M = bT for some constant b 2 (0;1] and sample size T: It is shown that the nonstandard …xed-b limit distributions of such nonparametrically studentized tests provide ...
SUN, Yixiao +2 more
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Wireless Network Optimization for Federated Learning with Model Compression in Hybrid VLC/RF Systems
In this paper, the optimization of network performance to support the deployment of federated learning (FL) is investigated. In particular, in the considered model, each user owns a machine learning (ML) model by training through its own dataset, and ...
Wuwei Huang +5 more
doaj +1 more source
Reduced Muscular Carnosine in Proximal Myotonic Myopathy—A Pilot 1H‐MRS Study
ABSTRACT Objective Myotonic dystrophy type 2 (proximal myotonic myopathy, PROMM) is a progressive multisystem disorder with muscular symptoms (proximal weakness, pain, myotonia) and systemic manifestations such as diabetes mellitus, cataracts, and cardiac arrhythmias.
Alexander Gussew +11 more
wiley +1 more source
Trajectories of Physical Function in Canadian Children with Juvenile Idiopathic Arthritis
Objectives We describe trajectories of physical function in children newly diagnosed with juvenile idiopathic arthritis (JIA) and identify trajectories with persisting functional impairments and associated baseline characteristics. Methods We included patients enrolled in the Canadian Alliance of Pediatric Rheumatology Investigators (CAPRI) Registry ...
Clare Cunningham +14 more
wiley +1 more source

