Ultrahigh dimensional time course feature selection

DOI10.1111/biom.12137zbMath1419.62482OpenAlexW1785056673WikidataQ40822011 ScholiaQ40822011MaRDI QIDQ5170203

Yi Li, Li Xing Zhu, Pei-Rong Xu

Publication date: 22 July 2014

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2027.42/107512

zbMATH Keywords

generalized estimating equationsvariable selectioncorrelated datasure screening propertyultrahigh dimensionalitylongitudinal analysistime course data

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Estimation in multivariate analysis (62H12) Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)

Related Items (6)

Robust variable selection in semiparametric mean-covariance regression for longitudinal data analysis ⋮ A moving average Cholesky factor model in covariance modeling for composite quantile regression with longitudinal data ⋮ Nonparametric independence screening for ultra-high dimensional generalized varying coefficient models with longitudinal data ⋮ A selective overview of feature screening for ultrahigh-dimensional data ⋮ Feature screening in ultrahigh-dimensional partially linear models with missing responses at random ⋮ Variable screening for high dimensional time series

Cites Work

• Longitudinal data analysis using generalized linear models
• Model-Free Feature Screening for Ultrahigh-Dimensional Data
• Sure independence screening in generalized linear models with NP-dimensionality
• Principled sure independence screening for Cox models with ultra-high-dimensional covariates
• Asymptotics for generalized estimating equations with large cluster sizes
• Nonparametric feature screening
• Shrinkage estimation analysis of correlated binary data with a diverging number of parameters
• Asymptotic results with generalized estimating equations for longitudinal data
• GEE analysis of clustered binary data with diverging number of covariates
• Penalized Generalized Estimating Equations for High-Dimensional Longitudinal Data Analysis
• Joint Variable Selection for Fixed and Random Effects in Linear Mixed-Effects Models
• Penalized Estimating Equations
• Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Additive Models
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Feature Screening via Distance Correlation Learning

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