[Estimation non-paramétrique renouvellement–défaillance–dégradation simultanés avec des risques concurrents]
Nous proposons un modèle conjoint pour des données de dégradation linéaire à taux aléatoire et des défaillances à modalités multiples et compétitives, sous des hypothèses de renouvellement partiel. Les procédures d'estimation non-paramétrique pour les intensités et les probabilités de panne comme fonctions du niveau de dégradation sont données ce qui permet d'obtenir les propriétés asymptotiques des estimateurs.
A joint model for linear degradation and competing failure data with partial renewals is proposed. Non-parametric estimation procedures for failure intensities and failure probabilities as functions of degradation level are given. Asymptotic properties of the estimators are investigated.
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Vilijandas Bagdonavičius 1 ; Algimantas Bikelis 1 ; Vytautas Kazakevičius 1 ; Mikhail Nikulin 2, 3
@article{CRMATH_2006__342_1_63_0, author = {Vilijandas Bagdonavi\v{c}ius and Algimantas Bikelis and Vytautas Kazakevi\v{c}ius and Mikhail Nikulin}, title = {Non-parametric estimation from simultaneous renewal{\textendash}failure{\textendash}degradation data with competing risks}, journal = {Comptes Rendus. Math\'ematique}, pages = {63--68}, publisher = {Elsevier}, volume = {342}, number = {1}, year = {2006}, doi = {10.1016/j.crma.2005.11.001}, language = {en}, }
TY - JOUR AU - Vilijandas Bagdonavičius AU - Algimantas Bikelis AU - Vytautas Kazakevičius AU - Mikhail Nikulin TI - Non-parametric estimation from simultaneous renewal–failure–degradation data with competing risks JO - Comptes Rendus. Mathématique PY - 2006 SP - 63 EP - 68 VL - 342 IS - 1 PB - Elsevier DO - 10.1016/j.crma.2005.11.001 LA - en ID - CRMATH_2006__342_1_63_0 ER -
%0 Journal Article %A Vilijandas Bagdonavičius %A Algimantas Bikelis %A Vytautas Kazakevičius %A Mikhail Nikulin %T Non-parametric estimation from simultaneous renewal–failure–degradation data with competing risks %J Comptes Rendus. Mathématique %D 2006 %P 63-68 %V 342 %N 1 %I Elsevier %R 10.1016/j.crma.2005.11.001 %G en %F CRMATH_2006__342_1_63_0
Vilijandas Bagdonavičius; Algimantas Bikelis; Vytautas Kazakevičius; Mikhail Nikulin. Non-parametric estimation from simultaneous renewal–failure–degradation data with competing risks. Comptes Rendus. Mathématique, Volume 342 (2006) no. 1, pp. 63-68. doi : 10.1016/j.crma.2005.11.001. https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.1016/j.crma.2005.11.001/
[1] Statistical analysis of linear degradation and failure time data with multiple failure modes, Lifetime Data Anal., Volume 10 (2004), pp. 65-81
[2] Estimation from simultaneous degradation and failure data (B. Linquist; K.A. Doksum, eds.), Mathematical and Statistical Methods in Reliability, Series on Quality, Reliability and Engineering Statistics, vol. 7, World Scientific, 2003, pp. 301-318
[3] Accelerated Life Models, Chapman and Hall/CRC, Boca Raton, 2002
[4] Estimation in degradation models with explanatory variables, Lifetime Data Anal., Volume 7 (2001), pp. 85-103
[5] Joint modeling of longitudinal measurements and event time data, Biostatistics, Volume 1 (2002), pp. 465-480
[6] Mixture models for the joint distribution of repeated measures and event times, Statistics in Medicine, Volume 16 (1997), pp. 239-257
[7] Estimating the parameters in the Cox model when covariate variables are measured with error, Biometrics, Volume 54 (1998), pp. 1407-1419
[8] Limit Theorems for Stochastic Processes, Springer, New York, 1987
[9] W. Kahle, Statistical models for the degree of repair in incomplete repair models, in: Proceedings of the International Symposium on Stochastic Models in Reliability, Safety, Security and Logistics, Sami Shamoon College of Engineering, Beer Sheva, February 2005, pp. 15–17
[10] On a degradation–failure models for repairable items (M. Nikulin; N. Balakrishnan; M. Mesbah; N. Limnios, eds.), Parametric and Semiparametric Models with Applications to Reliability Survival Analysis, and Quality of Life, Birkhäuser, Boston, 2004, pp. 65-80
[11] An estimator of the proportional hazards model with multiple longitudinal covariates measured with error, Biostatistics, Volume 3 (2002), pp. 511-528
[12] A semiparametric estimator for the proportional hazards model with longitudinal covariates measured with error, Biometrika, Volume 88 (2001), pp. 447-458
[13] Jointly modeling longitudinal and event time data with application to acquired immunodeficiency syndrome, J. Amer. Statist. Assoc., Volume 96 (2001), pp. 895-905
[14] A joint model for survival and longitudinal data measured with error, Biometrics, Volume 53 (1997), pp. 330-339
[15] Joint analysis of longitudinal data comprising repeated measures and times to events, Appl. Statist., Volume 50 (2001), pp. 375-387
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