Results 121 to 130 of about 3,411,803 (296)
Vine copula knockoffs for variable selection in gene expression studies
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
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
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
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
Mitigating measurement error in misspecified small area models
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
Functional and Mechanistic Studies of the <i>EST</i> Gene in the Gonads of <i>Chlamys farreri</i>. [PDF]
Li Y, Cui W, Liu X.
europepmc +1 more source

