Results 71 to 80 of about 25,451 (177)
An Agnostic Look at Bayesian Statistics and Econometrics [PDF]
Bayesians and non-Bayesians, often called frequentists, seem to be perpetually at loggerheads on fundamental questions of statistical inference. This paper takes as agnostic a stand as is possible for a practising frequentist, and tries to elicit a ...
Russell Davidson
core
Testing Distributional Granger Causality With Entropic Optimal Transport
Journal of Time Series Analysis, EarlyView.ABSTRACT We develop a novel nonparametric test for Granger causality in distribution based on entropic optimal transport. Unlike classical mean‐based approaches, the proposed method directly compares the full conditional distributions of a response variable with and without the history of a candidate predictor.
Tao Wang
wiley +1 more source
Machine‐learning classification of motor unit types in the adult mouse
The Journal of Physiology, EarlyView.Abstract figure legend The goal of this study was to build an algorithm for machine‐learning classification of motor unit (MU) physiological type in the adult mouse. We made intracellular recordings of triceps surae (TS) motoneurons in anaesthetized adult mice and recorded MU isometric force and electromyographic (EMG) activity.
María de Lourdes Martínez‐Silva +5 more
wiley +1 more source
Climate Change Risks and Climate Adaptation in Agro‐Processing Enterprises
Climate Resilience and Sustainability, Volume 5, Issue 1, June 2026.Due to its profit‐driven focus, agro‐processing participation had no significant effect on climate change adaptation. Education emerged as a key driver, positively influencing participation and adaptation behaviours. The study recommends integrating climate strategies into training programs and prioritising education to enhance resilience.
Adrino Mazenda +3 more
wiley +1 more source
Subgroup Identification via Multiple Change Point Detection: Methods and Applications
WIREs Computational Statistics, Volume 18, Issue 2, June 2026.Subgroup identification methods facilitate the discovery of clinically meaningful subpopulations with differing disease progression, improving personalized risk assessment and treatment strategies. ABSTRACT Subgroup identification is a significant research area in statistics and machine learning, aiming to partition a heterogeneous population into more
Yaguang Li +3 more
wiley +1 more source
Analyzing Competing Risk Data Using the R timereg Package [PDF]
In this paper we describe flexible competing risks regression models using the comp.risk() function available in the timereg package for R based on Scheike et al. (2008).
Mei-Jie Zhang, Thomas H. Scheike
core +1 more source
Informed Dictionary‐Guided Monte Carlo Inversion for Robust and Reproducible Multidimensional MRI
Magnetic Resonance in Medicine, Volume 95, Issue 5, Page 2947-2962, May 2026.ABSTRACT Purpose To develop a robust and efficient multidimensional MRI (MD‐MRI) data processing framework for accurately estimating joint frequency‐dependent diffusion‐relaxation distributions, while overcoming computational limitations and noise instability inherent to Monte Carlo (MC) inversion.
Joon Sik Park +3 more
wiley +1 more source
Variable Selection in Mixed‐Effects Location‐Scale and Location‐Shift Models
Statistics in Medicine, Volume 45, Issue 10-12, May 2026.ABSTRACT When ordinal responses to questionnaires structured on the basis of Likert scales show differing variability or heterogeneity in subgroups of the population, appropriate regression approaches that are able to take this issue into account are the location‐scale and location‐shift model.
Moritz Berger, Maria Iannario
wiley +1 more source
Testing for Exogeneity in Nonlinear Threshold Models [PDF]
Most work in the area of nonlinear econometric modelling is based on a single equation and assumes exogeneity of the explanatory variables. Recently, work by Caner and Hansen (2003) and Psaradakis, Sola, and Spagnolo (2004) has considered the possibility
George Kapetanios
core
Developmental Science, Volume 29, Issue 3, May 2026.ABSTRACT Youths’ socioeconomic status (SES) correlates with academic, cognitive, and neural outcomes, partly driven by influences on the developmental environment not captured by caregiver income and education alone. Leveraging Adolescent Brain Cognitive Development (ABCD) study data (M = 11.92 years; total n = 8,764), this study took an exploratory ...
Analia Marzoratti +4 more
wiley +1 more source