Bayesian prediction of future number of failures based on finite mixture of general class of distributions. (English) Zbl 1241.62139
Summary: This paper is concerned with the Bayesian prediction problem of the number of components which will fail in a future time interval. The failure times are distributed according to a finite mixture of a general class of distributions. A type-I censored sample from this nonhomogeneous population and a general class of prior density functions are used. A one-sample scheme is used to predict the number of failures in a future time interval. An example of a finite mixture of \(k\) exponential components is given to illustrate our results.
MSC:
| 62N05 | Reliability and life testing |
| 62F15 | Bayesian inference |
| 62N01 | Censored data models |
| 65C60 | Computational problems in statistics (MSC2010) |
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