Results 171 to 180 of about 1,444,224 (250)
Optimal subsampling for regression with mixed‐type predictors
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
The Scaling Limit of Random Two-Connected Series-Parallel Maps. [PDF]
Amankwah D +4 more
europepmc +1 more source
Homophily‐adjusted social influence estimation
Abstract Homophily and social influence are two key concepts of social network analysis. Distinguishing between these phenomena is difficult, and approaches to disambiguate the two have been primarily limited to longitudinal data analyses. In this study, we provide sufficient conditions for valid estimation of social influence through cross‐sectional ...
Hanh T.D. Pham, Daniel K. Sewell
wiley +1 more source
False and partial Eisenstein-type series related to unimodal sequences. [PDF]
Bringmann K, Pandey BV, van Ittersum JW.
europepmc +1 more source
Abstract Homogeneous normalized random measures with independent increments represent a broad class of Bayesian nonparametric priors and thus are widely used. In this article, we obtain the strong law of large numbers, the central limit theorem (CLT), and the functional central limit theorem (fCLT) of such measures when the concentration parameter a ...
Junxi Zhang, Shui Feng, Yaozhong Hu
wiley +1 more source
Random coverage from within with variable radii, and Johnson-Mehl cover times. [PDF]
Penrose MD, Higgs F.
europepmc +1 more source
Extreme conditional quantile estimation for time series
Abstract We consider the estimation of an extreme conditional quantile QY(1−p|x0)$$ {Q}_Y\left(1-p|{x}_0\right) $$ for a heavy‐tailed distribution in the case of a strictly stationary time series (Xt,Yt)t∈ℤ$$ {\left({X}_t,{Y}_t\right)}_{t\in \mathbb{Z}} $$. Here, QY(·|x0)$$ {Q}_Y\left(\cdotp |{x}_0\right) $$ denotes the conditional quantile function of
Yuri Goegebeur +2 more
wiley +1 more source
On the Lavrentiev Gap for Manifold-Valued Maps. [PDF]
Antonini CA +2 more
europepmc +1 more source
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
Liquid-Vapor Transition in a Model of a Continuum Particle System with Finite-Range Modified Kac Pair Potential. [PDF]
He Q, Jauslin I, Lebowitz J, Peled R.
europepmc +1 more source

