Results 71 to 80 of about 1,589,421 (354)
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
doaj +1 more source
Mixed Spline Smoothing and Kernel Estimator in Biresponse Nonparametric Regression
International Journal of Mathematics and Mathematical Sciences, 2021 Mixed estimators in nonparametric regression have been developed in models with one response. The biresponse cases with different patterns among predictor variables that tend to be mixed estimators are often encountered.
Dyah P. Rahmawati +3 more
doaj +1 more source
Three-Dimensional Smoothed Particle Hydrodynamics Method for Simulating Free Surface Flows [PDF]
, 2013 In this paper, we applied an improved Smoothing Particle Hydrodynamics (SPH) method by using gradient kernel renormalization in three-dimensional cases. The purpose of gradient kernel renormalization is to improve the accuracy of numerical simulation by ...
Naa, Christian Fredy, Prayogo, Rizal Dwi
core +2 more sources
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
wiley +1 more source
Proceedings, 2018 Bootstrap methods are used for bandwidth selection in: (1) nonparametric kernel density estimation with dependent data (smoothed stationary bootstrap and smoothed moving blocks bootstrap), and (2) nonparametric kernel hazard rate estimation (smoothed ...
Inés Barbeito, Ricardo Cao
doaj +1 more source
Brain kernel: A new spatial covariance function for fMRI data
NeuroImage, 2021 A key problem in functional magnetic resonance imaging (fMRI) is to estimate spatial activity patterns from noisy high-dimensional signals. Spatial smoothing provides one approach to regularizing such estimates. However, standard smoothing methods ignore
Anqi Wu +6 more
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Targeted smoothing parameter selection for estimating average causal effects
, 2013 The non-parametric estimation of average causal effects in observational studies often relies on controlling for confounding covariates through smoothing regression methods such as kernel, splines or local polynomial regression.
de Luna, Xavier, Häggström, Jenny
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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
wiley +1 more source
The smooth colonel meets the reverend [PDF]
, 2008 Kernel smoothing techniques have attracted much attention and some notoriety in recent years. The attention is well deserved as kernel methods free researchers from having to impose rigid parametric structure on their data.
Kiefer, Nicholas M., Racine, Jeffrey S.
core
Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics
Advanced Functional Materials, EarlyView.Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha +18 more
wiley +1 more source