Results 61 to 70 of about 147,262 (309)

Classification of Gaussian spatio-temporal data with stationary separable covariances

Nonlinear Analysis, 2021
The novel approach to classification of spatio-temporal data based on Bayes discriminant functions is developed. We focus on the problem of supervised classifying of the spatiotemporal Gaussian random field (GRF) observation into one of two classes ...
Marta Karaliutė, Kęstutis Dučinskas
doaj   +1 more source

Comparative Effectiveness and Safety of Inebilizumab Versus Rituximab in AQP4‐IgG‐Positive NMOSD

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Rituximab (anti‐CD20, RTX) and inebilizumab (anti‐CD19, INE) represent B‐cell‐depleting therapies used for aquaporin‐4 antibody‐positive (AQP4‐IgG+) neuromyelitis optica spectrum disorder (NMOSD); however, direct comparative evidence remains limited.
Jie Lin, Binbin Xue, Dewei Xie, Jia Li, Juyuan Pan, Lanbing Zhu, Qiaowen Tong, Jing Lin, Ruofan Zhu, Xu Zhang, Junhui Xia, Xiang Li   +11 more
wiley   +1 more source

Estimating model error covariance matrix parameters in extended Kalman filtering [PDF]

Nonlinear Processes in Geophysics, 2014
The extended Kalman filter (EKF) is a popular state estimation method for nonlinear dynamical models. The model error covariance matrix is often seen as a tuning parameter in EKF, which is often simply postulated by the user.
A. Solonen, J. Hakkarainen, A. Ilin, M. Abbas, A. Bibov   +4 more
doaj   +1 more source

Differential Item Functioning on the Patient Health Questionnaire 8 by Disease Subtype, Language, Sex, and Age Among People With Systemic Sclerosis: A Scleroderma Patient‐Centered Intervention Network Cohort Study

Arthritis Care &Research, EarlyView.
Objective Somatic items used in depression assessments can potentially overlap with symptoms related to physical illness, including systemic sclerosis (SSc). No studies have looked at whether somatic depression items may be influenced by diffuse versus limited SSc disease subtypes, which are associated with varying degrees of symptom presentation.
Sophie Hu, Marie‐Eve Carrier, Marie‐Claude Geoffroy, Meira Golberg, Linda Kwakkenbos, Susan J. Bartlett, Catherine Fortuné, Amy Gietzen, Karen Gottesman, Geneviève Guillot, Laura K. Hummers, Amanda Lawrie‐Jones, Vanessa L. Malcarne, Michelle Richard, Maureen Sauvé, Luc Mouthon, Andrea Benedetti, Brett D. Thombs, on behalf of the SPIN Investigators, Claire E. Adams, Marie Hudson, Maureen D. Mayes, James Stempel, Robyn K. Wojeck, Christian Agard, Laurent Alric, Marc André, Floryan Beaslay, Elana J. Bernstein, Sabine Berthier, Lyne Bissonnette, Sophie Blaise, Eva Bories, Alessandra Bruns, Carlotta Cacciatore, Patricia Carreira, Marion Casadevall, Benjamin Chaigne, Lorinda Chung, Benjamin Crichi, Thylbert Deltombe, Christopher P. Denton, Tannvir Desroche, Robyn Domsic, James V. Dunne, Bertrand Dunogue, Regina Fare, Dominique Farge‐Bancel, Paul R. Fortin, Tracy Frech, Loraine Gauzère, Anne Gerber, Jessica K. Gordon, Brigitte Granel‐Rey, Aurélien Guffroy, Geneviève Gyger, Eric Hachulla, Daphna Harel, Monique Hinchcliff, Sabrina Hoa, Michael Hugues, Alena Ikic, Sindhu R. Johnson, Nader Khalidi, Kimberly S. Lakin, Marc Lambert, Maggie Larche, David Launay, Yvonne C. Lee, Paul Legendre, Catarina Leite, Hélène Maillard, Nancy Maltez, Joanne Manning, Isabelle Marie, Maria Martin Lopez, Thierry Martin, Ariel Masetto, Arsène Mekinian, Sheila Melchor Díaz, Morgane Mourguet, Christelle Nguyen, Karen Nielsen, Mandana Nikpour, Louis Olagne, Vincent Poindron, Janet Pope, Susanna Proudman, Grégory Pugnet, Loïc Raffray, François Rannou, Alexis Régent, Frederic Renou, Sébastien Rivière, David Robinson, Esther Rodríguez Almazar, Tatiana Sofia Rodríguez‐Reyna, Sophie Roux, Perrine Smets, Vincent Sobanski, Robert F. Spiera, Virginia Steen, Evelyn Sutton, Carter Thorne, Damien Vagner, John Varga, Pearce Wilcox, Vanessa Cook, Cassidy Dal Santo, Monica D'Onofrio, Elsa‐Lynn Nassar   +110 more
wiley   +1 more source

A blocking and regularization approach to high dimensional realized covariance estimation [PDF]

, 2009
We introduce a regularization and blocking estimator for well-conditioned high-dimensional daily covariances using high-frequency data. Using the Barndorff-Nielsen, Hansen, Lunde, and Shephard (2008a) kernel estimator, we estimate the covariance matrix ...
Hautsch, Nikolaus, Lada M. Kyj, Oomen, Roel C.A., Roel C. A. Oomen, Nikolaus Hautsch, Kyj, Lada M., Oomen, Roel C. A.   +6 more
core   +1 more source

Considering the impact of observation error correlation in ensemble square-root Kalman filter [PDF]

Brazilian Journal of Oceanography, 2019
Data assimilation has been developed into an effective technology that can utilize a large number of multi-source unconventional data. It cannot only provide the initial field for the ocean numerical prediction model, but also construct the ocean ...
Shaodong Zang, Jichao Wang
doaj   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 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, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

Covariance-Based Uncertainty Analysis of Reference Equations of State

, 2020
This work presents a detailed methodology for uncertainty analysis applied to a reference equation of states (EOSs) based on Helmholtz energy. With increasing interest in uncertainties of thermal process models, it is important to quantify the property ...
Shengwei Wang (5689142), Jens Abildskov (1409680), Gürkan Sin (1434667), Howard Cheung (8232219), Jérôme Frutiger (1434673), Ian H. Bell (1307499)   +5 more
core   +3 more sources

Spatial Regression with Covariate Measurement Error: A Semiparametric Approach [PDF]

Biometrics, 2016
Summary Spatial data have become increasingly common in epidemiology and public health research thanks to advances in GIS (Geographic Information Systems) technology. In health research, for example, it is common for epidemiologists to incorporate geographically indexed data into their studies. In practice, however, the spatially defined
Huque, MH, Bondell, HD, Carroll, RJ, Ryan, LM   +3 more
openaire   +4 more sources