Results 191 to 200 of about 165,977,654 (290)
Abstract Hybrid models (HMs) combine fundamental model (FM) equations with empirical components. These models can lead to improved predictions because they reduce process/model mismatch and can account for phenomena that are not considered in the FM equations.
Mouna Y. Harb, Kimberley B. McAuley
wiley +1 more source
Prospects for direct electron detectors in ultrafast electron diffraction and scattering experiments. [PDF]
Kremeyer L +5 more
europepmc +1 more source
Dynamic survival risk prediction with time‐varying high‐dimensional images
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 +7 more
wiley +1 more source
Nonlinear permuted Granger causality
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
A Fast and Parallelized Procedure for Checking Molecular Dynamics 3D Structure. [PDF]
Roe DR, Brooks BR.
europepmc +1 more source
Copula‐based joint modelling of emergency department visits with time‐varying dependence
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
Cyclicity of Binary Group Codes. [PDF]
García García B +2 more
europepmc +1 more source
On Euclidean rings of integers in cyclotomic fields.
openaire +2 more sources
Lasso for hierarchical polynomial models
Abstract The divisibility conditions implicit in a polynomial hierarchy suggest parameter constraints in regression. With this idea, we establish strong and weak hierarchies for both the lasso and relaxed lasso. Our proposal extends prior work on hierarchical lasso, which was mainly concerned with models of degree 2.
H. Maruri‐Aguilar, S. Lunagómez
wiley +1 more source
A novel approach to explore common prime divisor graphs and their degree based topological descriptor. [PDF]
Koam ANA, Haider A, Ahmad A, Ansari MA.
europepmc +1 more source

