Results 161 to 170 of about 626,155 (280)

Assessment of Gibbs Free Energy Calculation in PI‐Controlled Heating

open access: yesChemie Ingenieur Technik, EarlyView.
For description and control of chemical processes in lab or industry thermodynamic variable Gibbs free energy provides opportunity to compare and interpret phenomena, even on a quantitative level. In a case study for PI‐controlled heating, impacts on its limits from control delay until parameter quantization are highlighted and assessed.
Jannik Dutschke   +4 more
wiley   +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

Analyzing zero‐truncated recurrent event data by stratified regression with time‐varying coefficients

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract This article presents a strategy for conducting regression analysis of zero‐truncated recurrent event data. The research is partly motivated by a pediatric mental health care (PMHC) program based on administrative data. We are particularly interested in how the occurrence of an event depends on its past occurrences and the associated ...
Anqi A. Chen   +3 more
wiley   +1 more source

Vine copula knockoffs for variable selection in gene expression studies

open access: yesCanadian 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   +3 more
wiley   +1 more source

Learning sparse mixture‐of‐experts generalized linear models in ultrahigh dimensions

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract Motivated by the challenges of heterogeneity and high dimensionality in the analysis of modern data, we investigate continuous regularization methods for learning sparse mixture‐of‐experts generalized linear models (MoE‐GLM). Although there are foundational results about regularized estimators in a broad class of regression models including ...
Pengqi Liu, Abbas Khalili
wiley   +1 more source

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