P. K. Andersen, Ø. Borgan, R. Gill, and N. Keiding, Statistical Models Based on Counting Processes, 1993.
DOI : 10.1007/978-1-4612-4348-9

Y. Bengio and Y. Grandvalet, No unbiased estimator of the variance of the K-fold cross-validation, Journal of Machine Learning Research, vol.5, pp.1089-1105, 2004.

D. Commenges and A. Gégout-petit, Likelihood inference for incompletely observed stochastic processes: ignorability conditions. arXiv:math, 2005.

D. Commenges and A. Gégout-petit, Likelihood for generally coarsened observations from multi-state or counting process models, Scand. J. Statist, 2006.
URL : https://hal.archives-ouvertes.fr/hal-00194266

D. Commenges and P. Joly, Multi-state Model for Dementia, Institutionalization, and Death, Communications in Statistics - Theory and Methods, vol.38, issue.6, pp.1315-1326, 2004.
DOI : 10.1093/aje/152.1.59
URL : https://hal.archives-ouvertes.fr/inserm-00262030

D. Commenges, P. Joly, L. Letenneur, and J. Dartigues, Incidence and mortality of Alzheimer's disease or dementia using an illness-death model, Statistics in Medicine, vol.23, issue.2, pp.199-210, 2004.
DOI : 10.1002/sim.1709

D. Cox and F. O-'sullivan, Asymptotic Analysis of Penalized Likelihood and Related Estimators, The Annals of Statistics, vol.18, issue.4, pp.1676-1695, 1990.
DOI : 10.1214/aos/1176347872

P. Eggermont and V. Lariccia, Optimal convergence rates for Good's nonparametric likelihood density estimator, Ann. Statist, vol.27, pp.1600-1615, 1999.

P. Eggermont and V. Lariccia, Maximum penalized likelihood estimation, 2001.

R. D. Gill, M. J. Van-der-laan, and J. M. Robins, Coarsening at Random, Advances in Applied Probability, vol.30, issue.02, pp.255-294, 1997.
DOI : 10.1007/978-1-4684-6316-3_14

I. J. Good and R. A. Gaskins, Nonparametric Roughness Penalties for Probability Densities, Biometrika, vol.58, issue.2, pp.255-277, 1971.
DOI : 10.2307/2334515
URL : http://biomet.oxfordjournals.org/cgi/content/short/58/2/255

C. Gu, Penalized likelihood hazard estimation: a general procedure, 1996.
DOI : 10.1007/978-1-4612-2618-5_5

P. Hall, On Kullback-Leibler Loss and Density Estimation, The Annals of Statistics, vol.15, issue.4, pp.1491-1519, 1987.
DOI : 10.1214/aos/1176350606
URL : http://projecteuclid.org/download/pdf_1/euclid.aos/1176350606

P. Hougaard, Analysis of multivariate survival data, 2000.
DOI : 10.1007/978-1-4612-1304-8

J. Jacod, Multivariate point processes: predictable projection, Radon-Nikodym derivatives, representation of martingales, Zeitschrift f???r Wahrscheinlichkeitstheorie und Verwandte Gebiete, vol.34, issue.3, pp.235-253, 1975.
DOI : 10.1007/BF00536010

P. Joly and D. Commenges, A Penalized Likelihood Approach for a Progressive Three-State Model with Censored and Truncated Data: Application to AIDS, Biometrics, vol.51, issue.3, pp.887-890, 1999.
DOI : 10.1111/j.0006-341X.1999.00887.x
URL : https://hal.archives-ouvertes.fr/inserm-00182452

P. Joly, D. Commenges, C. Helmer, and L. Letenneur, A penalized likelihood approach for an illness-death model with interval-censored data: application to age-specific incidence of dementia, Biostatistics, vol.3, issue.3, pp.433-443, 2002.
DOI : 10.1093/biostatistics/3.3.433
URL : https://hal.archives-ouvertes.fr/inserm-00182448

O. Kallenberg, Foundations of modern probabilities, 2001.
DOI : 10.1007/978-1-4757-4015-8

C. Kooperberg and D. Clarkson, Hazard Regression with Interval-Censored Data, Biometrics, vol.53, issue.4, pp.1485-1494, 1997.
DOI : 10.2307/2533514

S. W. Lagakos, C. J. Sommer, and M. Zelen, Semi-Markov models for partially censored data, Biometrika, vol.65, issue.2, pp.311-317, 1978.
DOI : 10.1093/biomet/65.2.311

L. Cam, L. Yang, and G. , Asymptotics in Statistics, 2000.

L. Letenneur, V. Gilleron, D. Commenges, C. Helmer, J. Orgogozo et al., Are sex and educational level independent predictors of dementia and Alzheimer's disease? Incidence data from the PAQUID project, Journal of Neurology, Neurosurgery & Psychiatry, vol.66, issue.2, pp.177-183, 1999.
DOI : 10.1136/jnnp.66.2.177

B. Liquet and D. Commenges, Estimating the Expectation of the Log-Likelihood with Censored Data for Estimator Selection, Lifetime Data Analysis, vol.11, issue.4, pp.351-367, 2004.
DOI : 10.1007/s10985-004-4772-z

B. Liquet, J. Saracco, and D. Commenges, Selection between proportional and stratified hazards models based on expected log-likelihood, Computational Statistics, vol.6, issue.4, 2006.
DOI : 10.1007/s00180-007-0079-3
URL : https://hal.archives-ouvertes.fr/hal-00153829

B. Liquet, . Sakarovitch, and D. Commenges, Bootstrap Choice of Estimators in Parametric and Semiparametric Families: An Extension of EIC, Biometrics, vol.7, issue.1, pp.172-178, 2003.
DOI : 10.1111/1541-0420.00020

H. Müller and U. Stadtmüller, Generalized functional linear models, The Annals of Statistics, vol.33, issue.2, pp.774-805, 2005.
DOI : 10.1214/009053604000001156

O. Sullivan and F. , Fast Computation of Fully Automated Log-Density and Log-Hazard Estimators, SIAM Journal on Scientific and Statistical Computing, vol.9, issue.2, pp.363-379, 1988.
DOI : 10.1137/0909024

H. Ramlau-hansen, Smoothing Counting Process Intensities by Means of Kernel Functions, The Annals of Statistics, vol.11, issue.2, p.466, 1983.
DOI : 10.1214/aos/1176346152

T. Scheike, times, The Annals of Statistics, vol.29, issue.5, pp.1344-1380, 2001.
DOI : 10.1214/aos/1013203457

M. Van-der-laan and S. Dudoit, Unified cross-validation methodology for selection among estimators and a general cross-validated adaptive epsilon-net estimator: finite sample oracle inequalities and examples. Berkeley Division of Biostatistics working paper series, paper 130 Asymptotic optimality of likelihood-based cross-validation, Statistical Applications in Genetics and Molecular Biology, vol.3, issue.1, 2003.

D. Commenges and I. U. , Université Victor Segalen Bordeaux 2, 146 rue Léo Saignat