Variable selection and structure identification for additive models with longitudinal data
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DOI: 10.1007/s00180-024-01521-1
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- Eva Cantoni & Joanna Mills Flemming & Elvezio Ronchetti, 2005. "Variable Selection for Marginal Longitudinal Generalized Linear Models," Biometrics, The International Biometric Society, vol. 61(2), pages 507-514, June.
- Wei Pan, 2001. "Akaike's Information Criterion in Generalized Estimating Equations," Biometrics, The International Biometric Society, vol. 57(1), pages 120-125, March.
- Lian, Heng, 2012. "Shrinkage estimation for identification of linear components in additive models," Statistics & Probability Letters, Elsevier, vol. 82(2), pages 225-231.
- Xue, Lan & Qu, Annie & Zhou, Jianhui, 2010. "Consistent Model Selection for Marginal Generalized Additive Model for Correlated Data," Journal of the American Statistical Association, American Statistical Association, vol. 105(492), pages 1518-1530.
- Yichao Wu & Leonard A. Stefanski, 2015. "Automatic structure recovery for additive models," Biometrika, Biometrika Trust, vol. 102(2), pages 381-395.
- Wenjiang J. Fu, 2003. "Penalized Estimating Equations," Biometrics, The International Biometric Society, vol. 59(1), pages 126-132, March.
- Fan, Yali & Qin, Guoyou & Zhu, Zhongyi, 2012. "Variable selection in robust regression models for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 109(C), pages 156-167.
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Backfitting algorithm; Correlation matrix; Two-stage estimation;All these keywords.
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