Results 201 to 210 of about 101,932 (253)

Uniform in Bandwidth Consistency of the <i>L</i>¹-Modal Regression Estimator for High-Dimensional Data. [PDF]

Entropy (Basel)
Almulhim FA, Alamari MB, Laksaci A.
europepmc   +1 more source

Harnessing machine learning and optimization for informed chemical engineering decisions: A styrene reactor analysis

The Canadian Journal of Chemical Engineering, EarlyView.
This study shows that integrating multiple machine learning models with optimization and decision‐making improves chemical process design, and that a consensus‐based strategy across models provides more robust and reliable operating recommendations than any single model, especially under limited or noisy data conditions.
Farough Agin, Clémence Fauteux‐Lefebvre, Jules Thibault   +2 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

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

Inference for Deep Neural Network Estimators in Generalized Nonparametric Models. [PDF]

J Am Stat Assoc
Meng X, Li Y.
europepmc   +1 more source

Robust nonparametric regression for testing the equality of nonparametric regression curves

Applied Mathematical Sciences, 2018
openaire   +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

Comparing Two Categorical Gini Correlations with Applications to Classification Problems. [PDF]

Stat Pap (Berl)
Hewage S, Sang Y.
europepmc   +1 more source