Results 51 to 60 of about 1,617,710 (291)
New Bandwidth Selection for Kernel Quantile Estimators
Journal of Probability and Statistics, 2012 We propose a cross-validation method suitable for smoothing of kernel quantile estimators. In particular, our proposed method selects the bandwidth parameter, which is known to play a crucial role in kernel smoothing, based on unbiased estimation of a ...
Ali Al-Kenani, Keming Yu
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Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2018 Data smoothing is often required within the environmental data analysis. A number of methods and algorithms that can be applied for data smoothing have been proposed.
Martina Čampulová
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Graph Dilated Network with Rejection Mechanism
Applied Sciences, 2020 Recently, graph neural networks (GNNs) have achieved great success in dealing with graph-based data. The basic idea of GNNs is iteratively aggregating the information from neighbors, which is a special form of Laplacian smoothing.
Bencheng Yan, Chaokun Wang, Gaoyang Guo
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Advanced Functional Materials, EarlyView.Biofabrication aims at providing innovative technologies and tools for the fabrication of tissue‐like constructs for tissue engineering and regenerative medicine applications. By integrating multiple biofabrication technologies, such as 3D (bio) printing with fiber fabrication methods, it would be more realistic to reconstruct native tissue's ...
Waseem Kitana +2 more
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ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R
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
Performing the Kernel Method of Test Equating with the Package kequate
Journal of Statistical Software, 2013 In standardized testing it is important to equate tests in order to ensure that the test takers, regardless of the test version given, obtain a fair test.
Björn Andersson +2 more
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A new method of kernel-smoothing estimation of the ROC curve
, 2016 The receiver operating characteristic (ROC) curve is a popular graphical tool for describing the accuracy of a diagnostic test. Based on the idea of estimating the ROC curve as a distribution function, we propose a new kernel smoothing estimator of the ...
Michal Pulit
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Advanced Functional Materials, EarlyView.The study presents biodegradable and recyclable mixed‐matrix membranes (MMMs), hydrogels, and cryogels using luminescent nanoscale metal‐organic frameworks (nMOFs) and biopolymers. These bio‐nMOF‐MMMs combine europium‐based nMOFs as probes for the status of the materials with the biopolymers agar and gelatine and present alternatives to conventional ...
Moritz Maxeiner +4 more
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Nonparametric Range-Based Double Smoothing Spot Volatility Estimation for Diffusion Models
Complexity, 2020 We consider nonparametric spot volatility estimation for diffusion models with discrete high frequency observations. Our estimator is carried out in two steps.
Jingwei Cai
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Understanding Decoherence of the Boron Vacancy Center in Hexagonal Boron Nitride
Advanced Functional Materials, EarlyView.State‐of‐the‐art computations unravel the intricate decoherence dynamics of the boron vacancy center in hexagonal boron nitride across magnetic fields from 0 to 3 T. Five distinct regimes emerge, dominated by nuclear spin interactions, revealing optimal coherence times of 1–20 µs in the 180–350 mT range for isotopically pure samples.
András Tárkányi, Viktor Ivády
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