Variable selection and estimation for multivariate panel count data via the seamless‐${\it L}_{{\rm 0}}$ penalty |
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Authors: | Haixiang Zhang Jianguo Sun Dehui Wang |
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Institution: | 1. School of Mathematics, Jilin University, Changchun 130012, China;2. Department of Statistics, University of Missouri, Columbia, MO 65211, USA |
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Abstract: | This paper considers regression analysis of multivariate panel count data with the focus on variable selection and estimation of significant covariate effects. For the problem, we adopt the penalized estimating equation approach with a focus on the use of the seamless‐$L_0$ penalty. The proposed approach selects variables and estimates regression coefficients simultaneously and the asymptotic properties of the resulting estimates are established. The procedure can be easily carried out with the Newton–Raphson algorithm and is evaluated by simulation studies. Also it is applied to a motivating data set arising from a skin cancer study. The Canadian Journal of Statistics 41: 368–385; 2013 © 2013 Statistical Society of Canada |
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Keywords: | Estimating equation marginal mean model multivariate panel count data seamless‐$L_0$ variable selection MSC 2010: Primary 62N02 secondary 62H12 |
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