Variable selection and estimation for multivariate panel count data via the seamless-${\it L}_{{\rm 0}}$ penalty

DOI10.1002/CJS.11172zbMath1273.62124OpenAlexW1964971922MaRDI QIDQ2851574

Jianguo Sun, De-Hui Wang, Hai-xiang Zhang

Publication date: 11 October 2013

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/cjs.11172

zbMATH Keywords

estimating equationsmarginal mean model

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) Linear inference, regression (62J99) Estimation in survival analysis and censored data (62N02)

Related Items (10)

Robust estimation of semiparametric transformation model for panel count data ⋮ Variable selection via generalized SELO-penalized linear regression models ⋮ Joint analysis of panel count data with an informative observation process and a dependent terminal event ⋮ Robust variable selection of joint frailty model for panel count data ⋮ Focused and Model Average Estimation for Regression Analysis of Panel Count Data ⋮ Simultaneous estimation and variable selection for incomplete event history studies ⋮ Polynomial spline estimation of panel count data model with an unknown link function ⋮ Variable selection via generalized SELO-penalized Cox regression models ⋮ Analysis of panel count data with time-dependent covariates and informative observation process ⋮ Order shrinkage and selection for the INGARCH(p,q) model

Cites Work

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• The statistical analysis of interval-censored failure time data.
• Analysing panel count data with informative observation times
• Variable Selection for Panel Count Data via Non-Concave Penalized Estimating Function
• Semiparametric transformation models for multivariate panel count data with dependent observation process
• Regression analysis of multivariate panel count data
• The Analysis of Panel Data Under a Markov Assumption
• Regression Parameter Estimation from Panel Counts
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Tuning parameter selectors for the smoothly clipped absolute deviation method

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