Penalized spline smoothing in multivariable survival models with varying coefficients
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Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 49 (2005)
Issue (Month): 1 (April)
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Web page: http://www.elsevier.com/locate/csda
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Zongwu Cai, 2003. "Local Linear Estimation for Time-Dependent Coefficients in Cox's Regression Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics & Finnish Statistical Society & Norwegian Statistical Association & Swedish Statistical Association, vol. 30(1), pages 93-111.
- Cai, T. & Hyndman, R.J. & Wand, M.P., 2000. "Mixed Model-Based Hazard Estimation," Monash Econometrics and Business Statistics Working Papers 11/00, Monash University, Department of Econometrics and Business Statistics.
- J. G. Booth & J. P. Hobert, 1999. "Maximizing generalized linear mixed model likelihoods with an automated Monte Carlo EM algorithm," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(1), pages 265-285.
- Hwang, Ruey-Ching, 2012. "A varying-coefficient default model," International Journal of Forecasting, Elsevier, vol. 28(3), pages 675-688.
- Kuhlenkasper, Torben & Kauermann, Göran, 2010. "Duration of maternity leave in Germany: A case study of nonparametric hazard models and penalized splines," Labour Economics, Elsevier, vol. 17(3), pages 466-473, June.
- Costa, M.J. & Shaw, J.E.H., 2009. "Parametrization and penalties in spline models with an application to survival analysis," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 657-670, January.
- Torben Kuhlenkasper & Göran Kauermann, 2009. "Duration of Maternity Leave in Germany: A Case Study of Nonparametric Hazard Models and Penalized Splines," SOEPpapers on Multidisciplinary Panel Data Research 213, DIW Berlin, The German Socio-Economic Panel (SOEP).
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