Results 181 to 190 of about 9,718 (249)

A partial envelope approach for modelling multivariate spatial‐temporal data

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract In the new era of big data, modelling multivariate spatial‐temporal data is a challenging task due to both the high dimensionality of the features and complex associations among the responses across different locations and time points.
Reisa Widjaja   +3 more
wiley   +1 more source

Nonlinear permuted Granger causality

open access: yesCanadian 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

Circular MIMO antenna with ML-based bandwidth and isolation prediction for 6G communications. [PDF]

open access: yesSci Rep
Alam MM   +7 more
europepmc   +1 more source

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

open access: yesCanadian 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

Trophic transfer and egestion dynamics of microplastics in the Brachionus-Asplanchna rotifer system. [PDF]

open access: yesEnviron Monit Assess
Jiménez-Contreras J   +5 more
europepmc   +1 more source

Optimal subsampling for regression with mixed‐type predictors

open access: yesCanadian 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

Machine learning-driven discovery of optimal designs for water electrolysis devices. [PDF]

open access: yesSci Adv
Zhang Z   +7 more
europepmc   +1 more source

Large parameter asymptotic analysis for homogeneous normalized random measures with independent increments

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract Homogeneous normalized random measures with independent increments represent a broad class of Bayesian nonparametric priors and thus are widely used. In this article, we obtain the strong law of large numbers, the central limit theorem (CLT), and the functional central limit theorem (fCLT) of such measures when the concentration parameter a ...
Junxi Zhang, Shui Feng, Yaozhong Hu
wiley   +1 more source

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