Bayesian nonparametric estimation of hazard rate in monotone Aalen model

Jana Timková

Kybernetika (2014)

  • Volume: 50, Issue: 6, page 849-868
  • ISSN: 0023-5954

Abstract

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This text describes a method of estimating the hazard rate of survival data following monotone Aalen regression model. The proposed approach is based on techniques which were introduced by Arjas and Gasbarra [4]. The unknown functional parameters are assumed to be a priori piecewise constant on intervals of varying count and size. The estimates are obtained with the aid of the Gibbs sampler and its variants. The performance of the method is explored by simulations. The results indicate that the method is applicable on small sample size datasets.

How to cite

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Timková, Jana. "Bayesian nonparametric estimation of hazard rate in monotone Aalen model." Kybernetika 50.6 (2014): 849-868. <http://eudml.org/doc/262143>.

@article{Timková2014,
abstract = {This text describes a method of estimating the hazard rate of survival data following monotone Aalen regression model. The proposed approach is based on techniques which were introduced by Arjas and Gasbarra [4]. The unknown functional parameters are assumed to be a priori piecewise constant on intervals of varying count and size. The estimates are obtained with the aid of the Gibbs sampler and its variants. The performance of the method is explored by simulations. The results indicate that the method is applicable on small sample size datasets.},
author = {Timková, Jana},
journal = {Kybernetika},
keywords = {monotone Aalen model; Bayesian estimation; Gibbs sampler; small sample size; monotone Aalen model; Bayesian estimation; Gibbs sampler; small sample size},
language = {eng},
number = {6},
pages = {849-868},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Bayesian nonparametric estimation of hazard rate in monotone Aalen model},
url = {http://eudml.org/doc/262143},
volume = {50},
year = {2014},
}

TY - JOUR
AU - Timková, Jana
TI - Bayesian nonparametric estimation of hazard rate in monotone Aalen model
JO - Kybernetika
PY - 2014
PB - Institute of Information Theory and Automation AS CR
VL - 50
IS - 6
SP - 849
EP - 868
AB - This text describes a method of estimating the hazard rate of survival data following monotone Aalen regression model. The proposed approach is based on techniques which were introduced by Arjas and Gasbarra [4]. The unknown functional parameters are assumed to be a priori piecewise constant on intervals of varying count and size. The estimates are obtained with the aid of the Gibbs sampler and its variants. The performance of the method is explored by simulations. The results indicate that the method is applicable on small sample size datasets.
LA - eng
KW - monotone Aalen model; Bayesian estimation; Gibbs sampler; small sample size; monotone Aalen model; Bayesian estimation; Gibbs sampler; small sample size
UR - http://eudml.org/doc/262143
ER -

References

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  1. Aalen, O. O., A model for nonparametric regression analysis of counting processes., Springer Lect. Notes in Statist. 2 (1980), 1-25. Zbl0445.62095MR0577267
  2. Aalen, O. O., 10.1002/sim.4780080803, Statist. Med. 8 (1989), 907-925. DOI10.1002/sim.4780080803
  3. Andersen, P. K., Borgan, A., Gill, R. D., Kieding, N., Statistical Models Based on Counting Processes., Springer, New York 1993. MR1198884
  4. Arjas, E., Gasbarra, D., Nonparametric bayesian inference from right censored survival data, using Gibbs sampler., Statist. Sinica 4 (1994), 505-524. MR1309427
  5. Cox, D. R., Regression models and life-tables., J. Roy. Statist. Soc. 34 (1972), 2, 187-220. Zbl0243.62041MR0341758
  6. Blasi, P. De, Hjort, N. L., 10.1111/j.1467-9469.2006.00543.x, Scand. J. Statist. 34 (2007), 229-257. Zbl1142.62077MR2325252DOI10.1111/j.1467-9469.2006.00543.x
  7. Blasi, P. De, Hjort, N. L., The Bernstein-von Mises theorem in semiparametric competing risks models., J. Statist. Planning Inf. 34 (2009), 1678-1700. Zbl1160.62023
  8. Doksum, K., Tailfree and neutral random probabilities and their posterior distributions., Ann. Statist. 2 (2006), 183-201. Zbl0279.60097MR0373081
  9. Green, P. J., 10.1093/biomet/82.4.711, Biometrika 82 (1995), 711-732. Zbl0861.62023MR1380810DOI10.1093/biomet/82.4.711
  10. Hjort, N. L., 10.1214/aos/1176347749, Ann. Stat. 3 (1990), 1259 - 1294. Zbl0711.62033MR1062708DOI10.1214/aos/1176347749
  11. Huffer, F. W., McKeague, I. W., 10.1080/01621459.1991.10475010, J. Amer. Statist. Assoc. 86 (1991), 114-129. DOI10.1080/01621459.1991.10475010
  12. Kaplan, E. L., Meier, P., 10.1080/01621459.1958.10501452, J. Amer. Statist. Assoc. 53 (1958), 457-481. Zbl0089.14801MR0093867DOI10.1080/01621459.1958.10501452
  13. Kim, Y., 10.1214/009053606000000533, Ann. Statist. 34 (2006), 1678-1700. Zbl1246.62050MR2283713DOI10.1214/009053606000000533
  14. Kim, Y., Lee, J., 10.1214/009053604000000526, Ann. Statist. 32 (2004), 1492-1512. Zbl1047.62043MR2089131DOI10.1214/009053604000000526
  15. Sinha, D., Dipak, K. D., 10.1080/01621459.1997.10474077, J. Amer. Statist. Assoc. 92 (1997), 1195-1212. Zbl1067.62520MR1482151DOI10.1080/01621459.1997.10474077
  16. Timková, J., Bayesian nonparametric estimation of hazard rate in survival analysis using Gibbs sampler., In: Proc. WDS 2008, Part I: Mathematics and Computer Sciences, pp. 80-87. 

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