Previous |  Up |  Next

Article

Title: An application of nonprarametric Cox regression model in reliability analysis: a case study (English)
Author: Volf, Petr
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 40
Issue: 5
Year: 2004
Pages: [639]-648
Summary lang: English
.
Category: math
.
Summary: The contribution deals with an application of the nonparametric version of Cox regression model to the analysis and modeling of the failure rate of technical devices. The objective is to recall the method of statistical analysis of such a model, to adapt it to the real–case study, and in such a way to demonstrate the flexibility of the Cox model. The goodness-of-fit of the model is tested, too, with the aid of the graphical test procedure based on generalized residuals. (English)
Keyword: hazard rate
Keyword: counting process
Keyword: Cox model
Keyword: nonparametric regression
Keyword: local likelihood
Keyword: time-to-failure
MSC: 05C90
MSC: 60G55
MSC: 62G08
MSC: 62N05
MSC: 90B25
idZBL: Zbl 1248.62193
idMR: MR2121002
.
Date available: 2009-09-24T20:04:38Z
Last updated: 2015-03-23
Stable URL: http://hdl.handle.net/10338.dmlcz/135622
.
Reference: [1] Andersen P. K., Borgan O., Gill R. D., Keiding N.: Statistical Models Based on Counting Processes.Springer, New York 1993 Zbl 0824.60003, MR 1198884
Reference: [2] Arjas E.: A graphical method for assesing goodnes of fit in Cox’s proportional hazard model.J. Amer. Statist. Assoc. 83 (1988), 204–212 10.1080/01621459.1988.10478588
Reference: [3] Arjas E., Liu L.: Assessing the losses caused by an industrial intervention – a hiearchical Bayesian approach.J. Roy. Statist. Soc. Ser. C 44 (1995), 357–368
Reference: [4] Fan J., Gijbels I.: Local Polynomial Modelling and Its Applications.Chapman and Hall, London 1996 Zbl 0873.62037, MR 1383587
Reference: [5] Gentleman R., Crowley J.: Local full likelihood estimation for the proportional hazard model.Biometrics 47 (1991), 1283–1296 MR 1157661, 10.2307/2532386
Reference: [6] Hastie T., Tibshirani R.: Generalized Additive Models.Chapman and Hall, London 1990 Zbl 0747.62061, MR 1082147
Reference: [7] Kalbfleisch J. D., Struthers C. A.: An analysis of the Reynolds Metals Company data.In: Case Studies in Data Analysis, Canad. J. Statist. 10 (1982), 237–259 10.2307/3556191
Reference: [8] Kooperberg C., Stone C. J., Truong Y. K.: The $L_2$ rate of convergence for hazard regression.Scand. J. Statist. 22 (1995), 143–157 MR 1339748
Reference: [9] Marzec L., Marzec P.: Generalized martingale-residual processes for goodness-of-fit inference in Cox’s type regression model.Ann. Statist. 25 (1997), 683–714 MR 1439319, 10.1214/aos/1031833669
Reference: [10] O’Sullivan F.: Nonparametric estimation in the Cox model.Ann. Statist. 21 (1993), 124–145 Zbl 0782.62046, MR 1212169, 10.1214/aos/1176349018
Reference: [11] Stone C. J.: The use of polynomial splines and their tensor products in multivariate function estimation; with discussion.Ann. Statist. 22 (1994), 118–184 Zbl 0827.62038, MR 1272079, 10.1214/aos/1176325361
Reference: [12] Thomas D. C.: Case analysis using Cox’s model.In: Case Studies in Data Analysis. Canad. J. Statist. 10 (1982), 237–259 10.2307/3556191
Reference: [13] Volf P.: A large sample study of nonparametric proportion hazard regression model.Kybernetika 29 (1993), 404–415 MR 1079678
Reference: [14] Volf P.: Analysis of generalized residuals in hazard regression models.Kybernetika 32 (1996), 501–510 Zbl 0882.62077, MR 1420139
.

Files

Files Size Format View
Kybernetika_40-2004-5_9.pdf 1.432Mb application/pdf View/Open
Back to standard record
Partner of
EuDML logo