Results 51 to 60 of about 55,286 (309)

Bandwidth Selection for Multivariate Kernel Density Estimation Using MCMC [PDF]

Kernel density estimation for multivariate data is an important technique that has a wide range of applications in econometrics and finance. However, it has received significantly less attention than its univariate counterpart.
Maxwell L. King,, Rob L. Hyndman, Xibin Zhang   +2 more
core   +2 more sources

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source

β-divergence loss for the kernel density estimation with bias reduced

Statistical Theory and Related Fields, 2021
In this paper, we investigate the problem of estimating the probability density function. The kernel density estimation with bias reduced is nowadays a standard technique in explorative data analysis, there is still a big dispute on how to assess the ...
Hamza Dhaker, El Hadji Deme, Youssou Ciss   +2 more
doaj   +1 more source

Creep‐Induced Microstructural Evolution in an A2‐B2 Superalloy

Advanced Engineering Materials, EarlyView.
A 27.3Ta‐27.3Mo‐27.3Ti‐8Cr‐10Al (at.%) refractory high‐entropy alloy with precipitation‐strengthened A2‐B2 microstructure was studied by creep tests at 1030°C, which demonstrate a transition in deformation mechanisms in the range of 100–150 MPa applied stress. This is associated with changes in dislocation–precipitate interactions. Relevant deformation
Liu Yang, Aparajita Pramanik, Sandipan Sen, Shubhashis Dixit, Marcel Muench, R. J. Vikram, Daniel Schliephake, Yolita M. Eggeler, Ankur Chauhan, Martin Heilmaier, Alexander Kauffmann   +10 more
wiley   +1 more source

Kernel density estimation for multiclass quantification

Machine Learning
fixed broken references to ...
Alejandro Moreo, Pablo González, Juan José del Coz   +2 more
openaire   +4 more sources

An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials

Advanced Engineering Materials, EarlyView.
An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut, Pierre Le Berre, Hamdi Jaballah, Lukas Fink, Victor Poline, Richard Haettel, Stéphane Grenier, Gilbert Chahine, Ewen Bellec, Guillaume Buatier, Wilfried Hortschitz, Santa Pile, Thomas Schrefl, Nils Blanc, Yuan Hong, Thibaut Devillers, Nora M. Dempsey   +16 more
wiley   +1 more source

Enhancing Bubble Removal in Geometry‐Optimized Electrodes

Advanced Engineering Materials, EarlyView.
3D‐printed lattice electrodes outperform stochastic foams in alkaline water electrolysis despite 20%–25% lower surface area. Straight flow channels generate Venturi‐like bubble entrainment, suppressing gas accumulation that renders foam interiors electrochemically inactive.
Florian Wiesner, Peter Förster, Alexander Limper, Anselm Brodersen, Matthias Wessling, John Linkhorst   +5 more
wiley   +1 more source

Asymptotic Properties of Error Density Estimators in the Two-Phase Linear Regression Model

Stats
This paper investigates kernel estimation of the error density function for the two-phase linear regression model. We derive the asymptotic distributions of residual-based kernel density estimators.
Fuxia Cheng, Lixia Wang
doaj   +1 more source

Fault Diagnosis of Rolling Bearings Based on EWT and KDEC

Entropy, 2017
This study proposes a novel fault diagnosis method that is based on empirical wavelet transform (EWT) and kernel density estimation classifier (KDEC), which can well diagnose fault type of the rolling element bearings.
Mingtao Ge, Jie Wang, Xiangyang Ren
doaj   +1 more source

A fast algorithm for sparse probability density function construction [PDF]

, 2013
A new sparse kernel density estimator is introduced. Our main contribution is to develop a recursive algorithm for the selection of significant kernels one at time using the minimum integrated square error (MISE) criterion for both kernel selection.
Xia Hong, Hong, Xia, Sheng Chen, Chen, Sheng   +3 more
core   +1 more source