Testing significance of random effects for the gamma degradation model
Gamma degradation models with fixed or random effects are widely used for reliability analysis. In this paper, the problem of testing significance of random effects for the gamma degradation model is considered. We propose two statistical tests which enable to reveal the existence of random effects in degradation data corresponding to the gamma degradation model. The first test is the well known likelihood ratio test and the second one is based on the variance estimate of the random parameter of the "random-effect" gamma degradation model. These tests have been compared in terms of power with Monte-Carlo simulation method. Moreover, the example of GaAs lasers degradation analysis has been considered.
Keywords
gamma degradation model,
fixed-effect model,
model with random effects,
reliability,
GaAs lasers,
деградационная гамма-модель,
модель с фиксированным эффектом,
модель со случайным эффектом,
надежность,
арсенид-галлиевые лазерыAuthors
Chetvertakova Evgeniia S. | Novosibirsk State Technical University | evgenia.chetvertakova@gmail.com |
Chimitova Ekaterina V. | Novosibirsk State Technical University | ekaterina.chimitova@gmail.com |
Всего: 2
References
Meeker, W.Q., Doganaksoy, N. & Hahn, G.J. (2009) Ispolzovanie dannykh o degradatsii dlya analiza nadezhnosti izdeliy [Using degradation data to analyze product reliability]. Metody menedzhmenta kachestva - Methods of Quality Management. 4.
Meeker, W.Q. & Escobar, L.A. (1998) Statistical Methods for Reliability Data. New York: John Wiley and Sons.
Chimitova, E., Chetvertakova, E., Sergeeva, S. & Osintseva, E. (2017) A comparative analysis of the Wiener, Gamma and Inverse Gaussian degradation models. Applied Methods of Statistical Analysis. Nonparametric methods in cybernetics and system analysis. Krasnoyarsk, Russia, September 18-22, 2017: Proc. of the Int. Workshop. Novosibirsk: NSTU. pp. 160-167.
Hausman, J.A. (1978) Specification Tests in Econometrics. Econometrica. 46. pp. 1251-1271.
Chimitova, E. & Chetvertakova, E. (2014) The construction of the gamma degradation model with covariates. Vestnik Tomskogo gosudarstvennogo universiteta. Upravlenie, vychislitel'naya tekhnika i informatika - Tomsk State University Journal of Control and Computer Science. 4(29). pp. 51-60.
Tsai, C.-C., Tseng, S.-T. & Balakrishnan, N. (2011) Mis-specification analyses of gamma and Wiener degradation processes. Journal of Statistical Planning and Inference. 12. pp. 25-35. DOI: 10.1016/j.jspi.2011.06.008
Chimitova, E.V. & Chetvertakova, E.S. (2015) A comparison of the "fixed-effect" and "random-effect" gamma degradation models. Applied methods of statistical analysis. Nonparametric approach, AMSA'2015, September 14-19, 2015: Proc. of the Int. Workshop. Novosibirsk. pp. 161 -169.
Tsai, C.-C., Tseng, S.-T. & Balakrishnan, N. (2012) Optimal Design for Degradation Tests Based on Gamma Processes with Random Effects. IEEE Trans. Reliab. 61. pp. 604-613. DOI: 10.1109/TR.2012.2194351
Antonov, A.V. & Nikulin, M.S. (2012) Statisticheskie modeli v teorii nadezhnosti [Statistical models in reliability theory]. Moscow: Abris.
Lawless, J. & Crowder, M. (2004) Covariates and Random Effects in a Gamma Process Model with Application to Degradation and Failure. Life Data Analysis. 10. pp. 213-227. DOI: 10.1023/B:LIDA.0000036389.14073.dd.
Nikulin, M. & Bagdonavicius, V. (2001) Accelerated Life Models: Modeling and Statistical Analysis. Boca Raton: Chapman & Hall/CRC.