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Prediction Intervals for Proportional Hazard Rate Models Based on Progressively Type II Censored Samples
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 Title & Authors
Prediction Intervals for Proportional Hazard Rate Models Based on Progressively Type II Censored Samples
Asgharzadeh, A.; Valiollahi, R.;
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 Abstract
In this paper, we present two methods for obtaining prediction intervals for the times to failure of units censored in multiple stages in a progressively censored sample from proportional hazard rate models. A numerical example and a Monte Carlo simulation study are presented to illustrate the prediction methods.
 Keywords
Progressive Type-II censoring;proportional hazard rate model;prediction interval;highest conditional density;Monte Carlo simulation;
 Language
English
 Cited by
1.
Predictions for Progressively Type-II Censored Failure Times from the Half Triangle Distribution,;;

Communications for Statistical Applications and Methods, 2014. vol.21. 1, pp.93-103 crossref(new window)
1.
Inference for the two-parameter half-logistic distribution using pivotal quantities under progressively type-ii censoring schemes, Communications in Statistics - Simulation and Computation, 2016, 0  crossref(new windwow)
2.
Predictions for Progressively Type-II Censored Failure Times from the Half Triangle Distribution, Communications for Statistical Applications and Methods, 2014, 21, 1, 93  crossref(new windwow)
 References
1.
Ahmadi, J., Jafari Jozani, M., Marchand, E. and Parsian, A. (2009a). Prediction of k-records from a general class of distributions under balanced type loss functions, Metrika, 70, 19-33. crossref(new window)

2.
Ahmadi, J., Jafari Jozani, M., Marchand, E. and Parsian, A. (2009b). Bayesian estimation based on k-record data from a general class of distributions under balanced type loss functions, Journal of Statistical Planning and Inference, 139, 1180-1189. crossref(new window)

3.
Awad, A. M. and Raqab, M. Z. (2000). Prediction intervals for the future record values from exponential distribution: Comparative study, Journal of Statistical Computation and Simulation, 65, 325-340. crossref(new window)

4.
Balakrishnan, N. (2007). Progressive censoring methodology: An appraisal, Test, 16, 211-259. crossref(new window)

5.
Balakrishnan, N. and Lin, C. T. (2002). Exact linear inference and prediction for exponential distributions based on general progressively Type-II censored samples, Journal of Statistical Computation and Simulation, 72, 677-686. crossref(new window)

6.
Basak, I., Basak, P. and Balakrishnan, N. (2006). On some predictors of times to failure of censored items in progressively censored samples, Computational Statistics & Data Analysis, 50, 1313-1337. crossref(new window)

7.
Marshall, A. W. and Olkin, I. (2007). Life Distributions, Springer, New York.

8.
Nelson, W. (1982). Applied Life Data Analysis, John Wiley & Sons, New York.

9.
Ng, H. K. T., Chan, P. S. and Balakrishnan, N. (2004). Optimal progressive censoring plans for the Weibull distribution, Technometrics, 46, 470-481. crossref(new window)

10.
Raqab, M. Z. and Nagaraja, H. N. (1995). On some predictors of future order statistics, Metron, 53, 185-204.

11.
Viveros, R. and Balakrishnan, N. (1994). Interval estimation of life characteristics from progressively censored data, Technometrics, 36, 84-91. crossref(new window)