Validation croisée pour l'estimateur lissé de la fonction de hasard : cas des données censurées

Salima Taibi-Hassani; Élie Youndjé

Revue de Statistique Appliquée (2003)

  • Volume: 51, Issue: 1, page 73-86
  • ISSN: 0035-175X

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Taibi-Hassani, Salima, and Youndjé, Élie. "Validation croisée pour l'estimateur lissé de la fonction de hasard : cas des données censurées." Revue de Statistique Appliquée 51.1 (2003): 73-86. <http://eudml.org/doc/106530>.

@article{Taibi2003,
author = {Taibi-Hassani, Salima, Youndjé, Élie},
journal = {Revue de Statistique Appliquée},
language = {fre},
number = {1},
pages = {73-86},
publisher = {Société française de statistique},
title = {Validation croisée pour l'estimateur lissé de la fonction de hasard : cas des données censurées},
url = {http://eudml.org/doc/106530},
volume = {51},
year = {2003},
}

TY - JOUR
AU - Taibi-Hassani, Salima
AU - Youndjé, Élie
TI - Validation croisée pour l'estimateur lissé de la fonction de hasard : cas des données censurées
JO - Revue de Statistique Appliquée
PY - 2003
PB - Société française de statistique
VL - 51
IS - 1
SP - 73
EP - 86
LA - fre
UR - http://eudml.org/doc/106530
ER -

References

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  1. [1] Ahmad I.A. (1976), Uniform strong convergence of the generalized failure rate estimate. Bull. Math. Statist., 17, pp. 77-84. Zbl0367.62045MR440781
  2. [2] Ango-Nzé P. (1994), Critères d'ergodicité de modèles markoviens. Estimation non paramétrique sous hypothèses de dépendance. Thèse à Univ Paris IX, France. 
  3. [3] Cai Z. et Roussas G.G. (1992), Uniform strong estimation under α-mixing, with rates. Stat. and Prob. Lett., pp. 47-55. Zbl0757.62024
  4. [4] Collomb G. (1976), Estimation non paramétrique de la régression par la méthode du noyau. Thèse à Univ. P. Sabatier, Toulouse, France. 
  5. [5] Droesbeke J.J., Fichet B. et Tassi P. (1989), Analyse statistique des durées de vie. Ed. Economica. MR1030997
  6. [6] Epanechnikov V. (1969), Nonparametric estimates of a multivariate probability density. Theory Probab. Appl.14, pp. 153 -158. Zbl0175.17101
  7. [7] Fermanian J.D. (1996), Choix d'une fenêtre optimale en n1/2 pour l'estimateur non paramétrique des fonctions de hasard, XVIIème Rencontre Franco-Belge de Statisticiens, Marne-la-Vallée. 
  8. [8] Grégoire G. (1993), Least squares Cross-Validation for counting process intensities. Scan. J. of Statist., 20, pp. 343- 360. Zbl0795.62031MR1276698
  9. [9] Hassani S., Sarda P. et Vieu P. (1986), Approche non paramétrique en théorie de la fiabilité. Rev. Statist. Appl., 35, pp. 27- 41. Zbl0609.62127MR878935
  10. [10] Härdle W. et Marron J.S. (1985), Optimal bandwidth selection in nonparametric regression function. Ann. Statist., 13, pp. 1465-1481. Zbl0594.62043MR811503
  11. [11] Lejeune M. et Sarda P. (1992), Smooth estimation of distribution and density function. Comp. Statist. Data Analysis, 14, pp. 457-471. Zbl0937.62581MR1192215
  12. [12] Marron J.S. et Padgett W.J. (1987), Asymptotically optimal bandwidth selection for kernel density estimators from randomly right censored samples. Ann. Statist., 15, pp. 1520-1535. Zbl0657.62038MR913571
  13. [13] Marron J.S. et Härdle W. (1986), Random approximations of some measure of accuracy in nonparametric curve estimation. J of Multiv. Ana., 19, pp. 1-13. MR862243
  14. [14] Marron J.S. et Wand M.P. (1992), Exact mean integrated squared errors. Ann. Statist., 20, pp. 712- 736. Zbl0746.62040MR1165589
  15. [15] Murthy V.K. (1965), Estimation of jumps, reliability and hazard rate. Ann. Statist., 36, pp. 1032-1040. Zbl0134.36103MR177474
  16. [16] Patil P.N. (1993a), Bandwidth choice for nonparametric hazard rate estimation. J. Statist. Plann. Inference, 35, pp. 15- 30. Zbl0777.62042MR1220402
  17. [17] Patil P.N. (1993b), On the least squares cross-validation bandwidth in hazard rate estimation. Ann. Statist., 21, pp. 1792-1810. Zbl0795.62041MR1245769
  18. [18] Patil P.N., Wells M.T. et Marron J.S. (1994), Some heuristic of kernel based estimators of ratio functions. Nonparametric Statist., 4, pp. 203 -209. Zbl05143440MR1290930
  19. [19] Sarda P. et Vieu P. (1991), Smoothing parameter selection in hazard estimation. Stat. and Prob. Lett., pp. 429-434. Zbl0724.62043MR1114533
  20. [20] Singpurwalla N.D. et Wong M.Y. (1983), Kernels estimators of the failure rate and density estimation : an analogy. J.A.S.A vol. 78, n° 382. Zbl0523.62034MR711128
  21. [21] Tanner M.A. et Wong W.H. (1983), The estimation of the hazard function from randomly censored data by kernel method. Ann. Statist., 11, pp. 989-993. Zbl0546.62017MR707949
  22. [22] Vieu P. (1991), Quadratic errors for nonparametric estimates under dependence. J. of Multiv. Ana., vol. 39, pp. 324-347. Zbl0751.62022MR1147126
  23. [23] Watson G.S. et Leadbetter M.R. (1964a), Hazard analysis I. Biometrica, 51, pp. 175-184. Zbl0128.13503MR184335
  24. [24] Watson G.S. et Leadbetter M.R. (1964b), Hazard analysis II. Sankhya, Ser. A, 26, pp. 110 - 116. Zbl0138.13906MR184336
  25. [25] Winter B.B. (1979), Convergence rate of perturbed empirical distribution function. J. Appl. Prob., 16, pp. 163- 173. Zbl0403.60033MR520946
  26. [26] Youndjé É., Sarda P. et Vieu P. (1996), Optimal smooth hazard estimates. Test, vol 5, N.2, pp. 374-379. Zbl0882.62036MR1439728

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