## Proceedings of the International School of Physics "Enrico Fermi". |

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Page 125

Finally, when the

zero or one, the analysis becomes questionable. For example, in a nuclear

power plant, what does one learn about the probability of core melt (the ultimate ...

Finally, when the

**number of failures**in the allotted test time becomes small, likezero or one, the analysis becomes questionable. For example, in a nuclear

power plant, what does one learn about the probability of core melt (the ultimate ...

Page 153

Complete observation until a specified

popular plan consists of putting n items on test and observing the failure times of

the first k failures, where k is specified in advance. The motivation for following

this ...

Complete observation until a specified

**number of failures**have occurred. Apopular plan consists of putting n items on test and observing the failure times of

the first k failures, where k is specified in advance. The motivation for following

this ...

Page 171

We can verify that, whereas it is possible to accept H0 without observing a single

failure, the rejection of H0 calls for observing ... Let Ege{r) denote the expected

...

We can verify that, whereas it is possible to accept H0 without observing a single

failure, the rejection of H0 calls for observing ... Let Ege{r) denote the expected

**number of failures**to reach a decision when 0 is the mean life of the exponential...

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### Contents

System Eeliabujty | 3 |

Statistical Theory of Eeliablitt | 8 |

Definitions and characterizations | 12 |

Copyright | |

39 other sections not shown

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### Common terms and phrases

algorithm approach associated assume assumption Bayesian boundary points chain coherent system complex conjugate prior consider correctness defined denote detected discussed edited equations equivalence class ergodic errors example exponential distribution failure rate Fault Tree Analysis function gamma given human reliability IEEE Trans IFEA implementation increasing independent input domain integration interval likelihood Markov Markov chain matrix mean method modules monotone month2 N. D. Singpurwalla number of failures number of system NUMITEMS observed obtained operational output parameters phase Poisson Poisson process possible predictive prior distribution probability problem procedure Proschan R. E. Barlow random variables reliability growth models reliability theory renewal theory repair requirements sample sect sequence Software Eng software reliability software reliability models specification Stat statistical stochastic stochastic process subsection system failure system reliability techniques theorem tion tt tt values vector zero