Results 171 to 180 of about 16,705,604 (281)

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

Power Counting in the Spectral Action Matrix Model. [PDF]

open access: yesCommun Math Phys
Hekkelman EM, van Nuland TDH, Reimann J.
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

Maximal Minimal Spacing for Random Points. [PDF]

open access: yesJ Stat Phys
Cunden FD   +3 more
europepmc   +1 more source

Sparse maximum likelihood estimation of regression models

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract For regression model selection and estimation, we study a small set of candidate models of maximum likelihood from which all information criteria such as the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) choose their models.
Min Tsao
wiley   +1 more source

Order restricted row‐column cluster randomized design

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract This research introduces a novel two‐stage cluster randomized design, the order restricted row‐column cluster randomized design. The new design builds upon the cluster randomized block design by incorporating a second layer of blocking, achieved through ranking cluster units that are randomly sampled from the population.
Dalton Hopper   +2 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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