Results 211 to 220 of about 267,886 (283)

Lasso for hierarchical polynomial models

open access: yesCanadian Journal of Statistics, EarlyView.
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

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

Mitigating measurement error in misspecified small area models

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract In the framework of Small area estimation, we consider an area‐level model where a subset of covariates is measured with error. The extent of the error is assumed to be constant throughout the areas, and it is expressed by a scalar parameter γ$$ \gamma $$, which multiplies the deterministic covariance matrix of the estimator of the true ...
Diego Battagliese   +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

Z‐residuals diagnostics for Cox models: Functional‐form misspecification versus nonproportional hazards

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract Primary biliary cholangitis (PBC) is a progressive autoimmune cholestatic disease for which modelling death, with transplantation as a competing event, is clinically important. Cox proportional hazards (PH) models are widely used, but standard diagnostics detect lack of fit without distinguishing non‐PH from misspecified covariate functions ...
Tingxuan Wu, Cindy Feng, Longhai Li
wiley   +1 more source

Front Propagation Through a Perforated Wall

open access: yesCommunications on Pure and Applied Mathematics, EarlyView.
ABSTRACT We consider a bistable reaction– diffusion equation ut=Δu+f(u)$u_t=\Delta u +f(u)$ on RN${\mathbb {R}}^N$ in the presence of an obstacle K$K$, which is a wall of infinite span with many holes. More precisely, K$K$ is a closed subset of RN${\mathbb {R}}^N$ with smooth boundary such that its projection onto the x1$x_1$‐axis is bounded and that ...
Henri Berestycki   +2 more
wiley   +1 more source

A Geometric Characterization of Steady Laminar Flow

open access: yesCommunications on Pure and Applied Mathematics, EarlyView.
ABSTRACT We study the steady states of the Euler equations on the periodic channel or annulus. We show that if these flows are laminar (layered by closed non‐contractible streamlines which foliate the domain), then they must be either parallel or circular flows.
Theodore D. Drivas, Marc Nualart
wiley   +1 more source

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