Results 51 to 60 of about 165,608 (287)
ESTIMATOR KERNEL DALAM MODEL REGRESI NONPARAMETRIK
Jurnal Matematika, 2012 Analisis regresi nonparametrik merupakan metode pendugaan kurva regresi yang digunakan jika tidak ada informasi sebelumnya te,ntang benttrk kurva regresi atau tidak terikat pada asumsi bentuk fungsi tertentu.
I Komang Gede Sukarsa +1 more
doaj +1 more source
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
core +1 more source
Reproducing kernel Hilbert spaces and variable metric algorithms in PDE constrained shape optimisation [PDF]
, 2016 In this paper we investigate and compare different gradient algorithms designed for the domain expression of the shape derivative. Our main focus is to examine the usefulness of kernel reproducing Hilbert spaces for PDE constrained shape optimisation ...
Eigel, Martin, Sturm, Kevin
core +3 more sources
Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones
Advanced Engineering Materials, EarlyView.A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell +3 more
wiley +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
Advanced Engineering Materials, EarlyView.This study demonstrates how optimizing laser power, scanning speed, and hatching distance in laser powder bed fusion can boost the productivity of Inconel 718 manufacturing by up to 29% while maintaining mechanical integrity. The work delivers a validated process window and cost–time analysis, offering industry‐ready guidelines for efficient additive ...
Amir Behjat +7 more
wiley +1 more source
Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
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
doaj +1 more source