Results 131 to 140 of about 114,105 (252)

The Augmented Hat‐Matrix of Hierarchical Generalised Linear Models and Its Use in Leverage Diagnostics

International Statistical Review, EarlyView.
Summary Defining a ‘hat‐matrix’ for a model is essential in many model diagnostic procedures, as it acts as an orthogonal projector from the observation space to the model space. In this paper, we introduce a unique Hat‐matrix for the class of hierarchical generalised linear models (HGLMs), which includes, as a special case, the subclass of generalised
Gianfranco Lovison, Mariangela Sciandra, Alessandro Albano, Chiara Di Maria   +3 more
wiley   +1 more source

The Accuracy Smoothness Dilemma in Prediction: A Novel Multivariate M‐SSA Forecast Approach

Journal of Time Series Analysis, EarlyView.
ABSTRACT Forecasting presents a complex estimation challenge, as it involves balancing multiple, often conflicting, priorities and objectives. Conventional forecast optimization methods typically emphasize a single metric, such as minimizing the mean squared error (MSE), which may neglect other crucial aspects of predictive performance. To address this
Marc Wildi
wiley   +1 more source

Accountability in Government Use of AI: Citizen Concerns and Preferences

Public Administration, EarlyView.
ABSTRACT Government adoption of AI opens the “pandora's box” of accountability, a core aspect of public value. Despite the centrality of governmental AI accountability, citizens' concerns and preferences in holding governments accountable for AI usage remain poorly understood.
Naikang Feng, Yanto Chandra
wiley   +1 more source

Research on digital twin modeling method for combustion process based on model reduction

Case Studies in Thermal Engineering
In response to the difficulty in obtaining combustion information within coal-fired boiler furnaces, a method is proposed in this study to improve the reduced-order model using clustering segmentation. This approach aims to rapidly predict the combustion
Yue Zhang, Jiale Li
doaj   +1 more source

Exercise during 14 days of head down tilt bedrest attenuates motor unit impairments in older humans

Experimental Physiology, EarlyView.
Abstract Head‐down tilt bedrest (HDBR) models the effects of mechanical unloading on neuromuscular function. The efficacy of exercise in preserving motor unit (MU) function in older adults during HDBR remains unclear. This study investigated the effects of 14‐day HDBR on MU properties in older adults and the protective role of exercise.
Philippe St‐Martin, Jean‐Christophe Lagacé, Mathil Ruel, Ahmed Ghachem, Guillaume Léonard, Eleonor Riesco, Mathew Piasecki, Jamie S. McPhee, Isabelle J. Dionne   +8 more
wiley   +1 more source

Beyond Beer‐Lambert Linear Regression: Multi‐Layer Modeling for Wide‐Range Concentration Quantification Using Ultraviolet‐visible Spectroscopy

Analytical Science Advances, Volume 7, Issue 1, June 2026.
ABSTRACT Ultraviolet–visible (UV‐Vis) spectroscopy is widely used for chemical quantification due to its simplicity and low cost; however, accurate concentration prediction becomes challenging when target concentrations span wide ranges, where the global linearity assumption of the Beer‐Lambert law often breaks down.
Muhammed ALjifri, Carter Miller, Yanjun Qian, Ye Chen, Mo Jiang   +4 more
wiley   +1 more source

Building a Digital Twin for Material Testing: Model Reduction and Data Assimilation

Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.
ABSTRACT The rapid advancement of industrial technologies, data collection, and handling methods has paved the way for the widespread adoption of digital twins (DTs) in engineering, enabling seamless integration between physical systems and their virtual counterparts.
Rubén Aylwin, Nina Beranek, Gajendra Babu Budihala, Matthias Mettenleiter, Goksu Oruc, Karsten Urban   +5 more
wiley   +1 more source

Nonlinear Model Order Reduction on Polynomial Manifolds for Computational Homogenisation Problems

Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.
ABSTRACT Model order reduction (MOR) techniques utilising nonlinear approximation spaces can search for solutions to computational homogenisation problems on low‐dimensional approximation spaces. In combination with hyperreduction techniques, this allows for computations on representative volume elements (RVEs) to be accelerated by multiple orders of ...
Erik Faust, Lisa Scheunemann
wiley   +1 more source

On the Foundational Arguments of Sufficient Dimension Reduction

WIREs Computational Statistics, Volume 18, Issue 2, June 2026.
Contemporary Sufficient Dimension Reduction, a versatile method for extracting material information from data, can serve as a preprocessor for classical modeling and inference, or as a standalone theory that leads directly to statistical inference. ABSTRACT Sufficient dimension reduction (SDR) refers to supervised methods of dimension reduction that ...
R. Dennis Cook
wiley   +1 more source

Infinity‐operadic foundations for embedding calculus

Journal of Topology, Volume 19, Issue 2, June 2026.
Abstract Motivated by applications to spaces of embeddings and automorphisms of manifolds, we consider a tower of ∞$\infty$‐categories of truncated right modules over a unital ∞$\infty$‐operad O$\mathcal {O}$. We study monoidality and naturality properties of this tower, identify its layers, describe the difference between the towers as O$\mathcal {O}$
Manuel Krannich, Alexander Kupers
wiley   +1 more source