Results 81 to 90 of about 6,156 (248)

Sustainable and Resilient Supply Networks: Digitalisation, Regulation and Climate Vulnerability in a Global Context

Business Strategy and the Environment, EarlyView.
ABSTRACT The growing frequency of global crises has intensified concerns regarding climate vulnerability and the resilience of global production systems. This study examines the heterogeneous effects of supply chain development and supply chain digitalisation on climate vulnerability across countries, while accounting for institutional and investment ...
Ziwei Li, Zhi Zhan, Kingsley Imandojemu, Romanus Osabohien, Damilola Felix Eluyela   +4 more
wiley   +1 more source

Rehabilitation After Stroke in a Transition From Hospital to Municipality—Impact of Amount of Rehabilitation

Chronic Diseases and Translational Medicine, EarlyView.
Measurements obtained throughout the study, from acute hospitalization to the end of rehabilitation in the municipalities. The intervals between assessments are approximate. The lower boxes indicate the assessments performed. ABSTRACT Background Stroke is a leading cause of long‐term disability that impairs physical function and health‐related quality ...
Gabriel Tafdrup Notkin, Dorthe Gaby Bove, Lisbet Lind, Michael Broksgaard Jensen, Stig Molsted   +4 more
wiley   +1 more source

Dynamic survival risk prediction with time‐varying high‐dimensional images

Canadian Journal of Statistics, EarlyView.
Abstract Integrating longitudinal data with survival models is a prevalent strategy for dynamic survival risk prediction while accounting for subjects' longitudinally observed variables. However, existing methods primarily focus on scalar longitudinal data and seldom tackle the complexities associated with high‐dimensional longitudinal imaging data ...
Bingfan Liu, Haolun Shi, Shu Jiang, Liangliang Wang, Da Ma, Mirza Faisal Beg, Jiguo Cao, for the Alzheimer's Disease Neuroimaging Initiative   +7 more
wiley   +1 more source

Nonparametric Inference for Time-Varying Coefficient Quantile Regression

Journal of Business & Economic Statistics, 2017
The article considers nonparametric inference for quantile regression models with time-varying coefficients. The errors and covariates of the regression are assumed to belong to a general class of locally stationary processes and are allowed to be cross-dependent.
Zhou, Zhou, Wu, Weichi
openaire   +1 more source

Nonlinear permuted Granger causality

Canadian Journal of Statistics, EarlyView.
Abstract Granger causality is an established, contentious method that seeks causal temporal connections via association and precedence. While not true causal inference, it assists in mapping networks of information flow that may warrant further study.
Noah D. Gade, Jordan Rodu
wiley   +1 more source

Copula‐based joint modelling of emergency department visits with time‐varying dependence

Canadian Journal of Statistics, EarlyView.
Abstract Jointly modelling multiple correlated count time series is essential in health services research, where outcomes like emergency visits for mental health and substance use often evolve together. Ignoring these dependencies can obscure meaningful trends and limit the effectiveness of policy evaluation.
Guanjie Lyu, Cindy Feng, Lihui Liu
wiley   +1 more source

Reference Charts for Fetal Cerebellar Vermis Height: A Prospective Cross-Sectional Study of 10605 Fetuses. [PDF]

PLoS ONE, 2016
OBJECTIVE:To establish reference charts for fetal cerebellar vermis height in an unselected population. METHODS:A prospective cross-sectional study between September 2009 and December 2014 was carried out at ALTAMEDICA Fetal-Maternal Medical Centre, Rome,
Pietro Cignini, Maurizio Giorlandino, Pierpaolo Brutti, Lucia Mangiafico, Alessia Aloisi, Claudio Giorlandino   +5 more
doaj   +1 more source

Vine copula knockoffs for variable selection in gene expression studies

Canadian Journal of Statistics, EarlyView.
Abstract Identifying clinical and genetic markers is essential for stratifying cancer patients by survival outcomes and guiding personalized treatment strategies. However, gene expression studies often involve high‐dimensional predictors with mixed data types and complex dependence, which complicates reliable variable selection.
José Ulises Márquez Urbina, Alejandro Román Vásquez, Graciela González Farías, Gabriel Escarela   +3 more
wiley   +1 more source

Optimal subsampling for regression with mixed‐type predictors

Canadian Journal of Statistics, EarlyView.
Abstract Subsampling has emerged as an appealing strategy to mitigate the computational and storage challenges imposed by large datasets. Recent subsampling techniques have shown notable computational gains for data dominated by numerical predictors. However, real‐world datasets frequently contain both numerical and categorical predictors.
Jiaqing Zhu, Lin Wang, Fasheng Sun
wiley   +1 more source

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models

Journal of Forecasting, EarlyView.
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly, Pooja Sengupta, Divya Aggarwal   +2 more
wiley   +1 more source