Results 51 to 60 of about 3,403,709 (354)
Optimal Bandwidth Selection for Kernel Density Functionals Estimation
Journal of Probability and Statistics, 2015 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
Proceedings, 2018 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
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Bandwidth selection for kernel conditional density estimation [PDF]
Computational Statistics & Data Analysis, 2001 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]
Econometrica, 2008 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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Nonparametric localized bandwidth selection for Kernel density estimation
, 2019 As conventional cross-validation bandwidth selection methods do not work properly in the situation where the data are serially dependent time series, alternative bandwidth selection methods are necessary.
Tingting Cheng, Jiti Gao, Xibin Zhang
semanticscholar +1 more source
Wireless Network Optimization for Federated Learning with Model Compression in Hybrid VLC/RF Systems
Entropy, 2021 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
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Optimal Relay Selection with Non-negligible Probing Time
, 2015 In this paper an optimal relay selection algorithm with non-negligible probing time is proposed and analyzed for cooperative wireless networks. Relay selection has been introduced to solve the degraded bandwidth efficiency problem in cooperative ...
Liu, Mingyan, Liu, Yang, Ouyang, Yi
core +1 more source
Reduced Muscular Carnosine in Proximal Myotonic Myopathy—A Pilot 1H‐MRS Study
Annals of Clinical and Translational Neurology, EarlyView.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
Bandwidth selection for kernel estimation in mixed multi-dimensional spaces [PDF]
, 2007 Kernel estimation techniques, such as mean shift, suffer from one major drawback: the kernel bandwidth selection. The bandwidth can be fixed for all the data set or can vary at each points.
Aurélie Bugeau +4 more
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International Journal of Adaptive Control and Signal Processing, EarlyView.This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley +1 more source