Results 31 to 40 of about 239,377 (84)

Partial Time‐Varying Regression Modelling Under General Heterogeneity

Journal of Time Series Analysis, EarlyView.
ABSTRACT This paper studies a semiparametric time‐varying regression model in which a subset of regressors is associated with fixed parameters, while the remaining regressors have parameters that evolve smoothly over time. We propose a closed‐form semiparametric Frisch‐Waugh‐Lovell estimator for the fixed parameters, and a non‐parametric kernel type ...
Liudas Giraitis, George Kapetanios, Yufei Li, Tien Chuong Nguyen   +3 more
wiley   +1 more source

From contamination to fever: The role of endotoxin levels in bacterially contaminated platelet concentrates

Vox Sanguinis, EarlyView.
Abstract Background and Objectives Growth of gram‐negative bacteria in a platelet concentrate (PC) is inevitably accompanied by the accumulation of endotoxin, which is the major component of the outer cell membrane of these organisms. However, less is known about the kinetics of endotoxin accumulation in PC and its biological activity.
Marcel Prax, Lea Debes, Paul Adomeit, Michel‐Andrés García‐Otálora, Carl P. McDonald, Marc Cloutier, Ute Gravemann, Opeyemi Adesina, Morenike Adeoye‐Isijola, Josephine Hubloher, Hellen Sarela, Tanja Vollmer, Oleg Krut, Sandra Ramirez‐Arcos, ISBT Transfusion‐Transmitted Infectious Diseases Working Party “Subgroup on Bacteria”   +14 more
wiley   +1 more source

Supporting AI Readiness Through Digital Workflows in Materials Science

Advanced Engineering Materials, Volume 28, Issue 20, 21 October 2026.
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns, Lateef Abdul, Stephan Barth, Martin Glauer, Manuel Günther, Fabian Neuhaus, Jan‐Ole Perschewski, Thomas Bjarsch, Henrik Abel, Johannes Bosch, Niklas Meyer, Peter Hofmann, Marc Drechsler, Alexander Dyck, Dhanunjaya Kumar Nerella, Marvin Tegeler, Oleg Shchyglo, Ingo Steinbach, Timo Klecker, Henk Birkholz, Ehsan Borzabadi Farahani, Bernard Fedelich, Cetin Haftaoglu, Tarakeshwar Lakshmipathy, Elena Garcia Trelles, Christoph Schweizer, Reza Darvishi Kamachali, Lukas Koschmieder, Janin Eiken, Markus Apel, Sung‐Min Wi, Jiangdong Zhao, Andreas Fezer, Nicolas Christ, Patrick Schneider, Eldor Urinov, Veit Königer, Volker Knoblauch, Janik Harter, Thomas Seifert, Thitichai Janpheng, Florian Fuchs, Fabian Teichert, Jörg Schuster, Anke Bardehle, Andreas Limper, Ulrich Giese, Carlos Lucke, Mario Beiner, Christoph Gögelein, Lisa Leuchtenberger‐Engel, Christian Hopmann, Felix Wentzien, Heike Wittek, Benjamin Klie, Alexander Röhrs, Ludger Overmeyer, Achraf Atila, Marcel Sadowski, Leopold Talirz, Jan Janssen, Jesper R. Pedersen, Peter Beck, Tejs Vegge, Ivano E. Castelli, Wolfgang Wenzel, Tilmann Hickel, Jörg Schaarschmidt   +67 more
wiley   +1 more source

Bayesian Exploration of Metal‐Organic Framework‐Derived Nanocomposites for High‐Performance Supercapacitors

Advanced Intelligent Discovery, Volume 2, Issue 5, October 2026.
An AI‐assisted approach is introduced to decode synthesis–performance relationships in metal‐organic framework‐derived supercapacitor materials using Bayesian optimization and predictive modeling, streamlining the search for optimal energy storage properties.
David Gryc, Pritam Banerjee, Felipe Jacques Lima Duarte, Joerg R. Jinschek, Premkumar Murugesan, Babak Rezaei, Stephan Sylvest Keller, Roland A. Fischer, Mian Zahid Hussain   +8 more
wiley   +1 more source

Multimodality in the GARCH Regression Model [PDF]

Several aspects of GARCH(p,q) models that are relevant for empirical applications are investigated. In particular, it is noted that the inclusion of dummy variables as regressors can lead to multimodality in the GARCH likelihood.
Jurgen A. Doornik, Marius Ooms
core  

Money growth, uncertainty and macroeconomic activity: a multivariate GARCH analysis

Money growth, Uncertainty, MV GARCH, Monetary analysis,
David Cronin, Robert Kelly, Bernard Kennedy   +2 more
core   +1 more source

Risk Transmission and Co‐Movements Between Financial Markets and Commodity Markets in the COVID‐19 Period

International Journal of Finance &Economics, Volume 31, Issue 4, Page 4667-4686, October 2026.
ABSTRACT This study examines risk transmission and co‐movements between financial markets (G7 countries and China) and commodity markets (gold and oil) during the COVID‐19 crisis. Daily closing prices for major equity indices (CAC40, CSI300, DAX30, FTSE100, MIB, NIKKEI, TSX and S&P500) and futures prices for gold, brent and WTI were analysed using DCC ...
V. Moutinho, H. Oliveira, M. Neves, J. Monteiro   +3 more
wiley   +1 more source

Regime switching GARCH models [PDF]

We develop univariate regime-switching GARCH (RS-GARCH) models wherein the conditional variance switches in time from one GARCH process to another. The switching is governed by a time-varying probability, specified as a function of past information.
Luc, BAUWENS, Jeroen, ROMBOUTS, Arie, PREMINGER   +2 more
core  

Wake me up before you GO-GARCH [PDF]

In this paper we present a new three-step approach to the estimation of Generalized Orthogonal GARCH (GO-GARCH) models, as proposed by van der Weide (2002).
Boswijk, H.P., Weide, R. van der
core  

Forecasting the time-varying beta of UK firms: GARCH models vs Kalman filter method

, 2007
This paper forecast the weekly time-varying beta of 20 UK firms by means of four different GARCH models and the Kalman filter method. The four GARCH models applied are the bivariate GARCH, BEKK GARCH, GARCH-GJR and the GARCH-X model.
Wu, Hao, Choudhry, Taufiq
core   +1 more source