Remuestreo Bootstrap y Jackknife en confiabilidad: Caso Exponencial y Weibull

Javier Ramírez-Montoya; Ignacio Osuna-Vergara; Jessica Rojas-Mora; Stalyn Guerrero-Gómez

doi:10.19053/01211129.4137

Vol. 25 No. 41 (2016)

Papers

Bootstrap and Jacknnife resampling in reliability: case exponential and Weibull

https://doi.org/10.19053/01211129.4137

Published 2016-01-22

Javier Ramírez-Montoya
Ignacio Osuna-Vergara
Jessica Rojas-Mora
Stalyn Guerrero-Gómez

Javier Ramírez-Montoya
Universidad de Sucre

Ignacio Osuna-Vergara
Universidad de Córdoba

Jessica Rojas-Mora
Universidad de Córdoba

Stalyn Guerrero-Gómez
Universidad Santo Tomás

How to Cite

Ramírez-Montoya, J., Osuna-Vergara, I., Rojas-Mora, J., & Guerrero-Gómez, S. (2016). Bootstrap and Jacknnife resampling in reliability: case exponential and Weibull. Revista Facultad de Ingeniería, 25(41), 55–62. https://doi.org/10.19053/01211129.4137

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Abstract

In this paper the resampling methods bootstrap-t, Jackknife delete I and delete II, are compared using the non-parametric estimators Kaplan-Meier and Nelson-Aalen, frequently used in the practice, taking into account different percentages of censorship, sample sizes and times of interest. The comparation is carried out by simulation, using the mean square error.

Keywords

Bootstrap, Jackknife, reliability function

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References

C. Arrabal, R. Da Rocha, R. Nonaka, S. Meira. “Comparison of resampling method applied to censored data”, International Journal of Advanced Statistics and Probability, Vol. 2, No. 2, pp. 48-55. 2014. DOI: http://dx.doi.org/10.14419/ijasp.v2i2.2291. DOI: https://doi.org/10.14419/ijasp.v2i2.2291
B. Efron. “Bootstrap methods: Another look at jackknife”, The Annals of Statistics, Vol. 7, pp. 1-26. 1979. DOI: http://dx.doi.org/10.1214/aos/1176344552. DOI: https://doi.org/10.1214/aos/1176344552
E. Kaplan and P. Meier. “Estimation from Incomplete Observations”, American Statistical Association, Vol. 53, pp. 457-481. 1958. DOI: http://dx.doi.org/10.1080/01621459.1958.10501452. DOI: https://doi.org/10.1080/01621459.1958.10501452
J. Lawless. Statistical Models and Methods for Lifetime Data. New York: Wiley and Sons, 2003. DOI: https://doi.org/10.1002/9781118033005
W. Meeker, L. Escobar. Statistical Models and Methods for Reliability Data. N.Y. John Wiley & Sons. 1998.
W. Nelson. “Hazard plotting for incomplete failure data”. Journal of Quality Technology, Vol. 61, pp. 27-52. 1969. DOI: https://doi.org/10.1080/00224065.1969.11980344
R Development Core Team. R: A Language and Environment for Statistical Computing”. 2007. R Foundation for Statistical Computing, Vienna, Austria. Avalaible: http://www.R-project.org.
J. Ramírez. “Comparación de intervalos de confianza para la función de supervivencia con censura a derecha”. Revista Colombiana de Estadística, Vol. 34, pp. 197-209. 2011.

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