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

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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 at least r* = [hj/s] -f- 1 failures; [j]

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

failure, the rejection of H0 calls for observing at least r* = [hj/s] -f- 1 failures; [j]

**denotes**the smallest integer greater than j. Let La(6)**denote**the probability of ...Page 180

In what follows, we show that, for w<w0, the producer (consumer) can gain more

protection when using the decision rule specified by (2.2) by increasing n when F

is IFR (DFR). Consider the accept and reject boundaries for the test, and

In what follows, we show that, for w<w0, the producer (consumer) can gain more

protection when using the decision rule specified by (2.2) by increasing n when F

is IFR (DFR). Consider the accept and reject boundaries for the test, and

**denote**...Page 209

Note that the expression on the left-hand side of the above equation

posterior distribution for 6 at time t, whereas the first and second expressions on

the right- hand side

Note that the expression on the left-hand side of the above equation

**denotes**theposterior distribution for 6 at time t, whereas the first and second expressions on

the right- hand side

**denote**the likelihood and the prior distribution for 0, ...### What people are saying - Write a review

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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