## Proceedings of the International School of Physics "Enrico Fermi", Volume 94 |

### From inside the book

Results 1-3 of 87

Page 129

over - simplified , and will , for the first time , have

embedded in them . There will always be an initiating event , with some

consequences of that ...

over - simplified , and will , for the first time , have

**probabilities**of failureembedded in them . There will always be an initiating event , with some

**probability**of occurrence , followed by an evaluation of the various possibleconsequences of that ...

Page 135

In the estimation of the

components of the calculation of which one knows very little , succeeded by

some about which one knows a great deal . For example , one may have no idea

about ...

In the estimation of the

**probability**of a complex event tree , one will often havecomponents of the calculation of which one knows very little , succeeded by

some about which one knows a great deal . For example , one may have no idea

about ...

Page 246

Consider the consequence [ di , 0 ; ] for sure vs . the gamble where C occurs with

the situation . . C [ di , 0 ; ] ~ Fig . 1 . – [ di , 0 ; ] for sure equivalent to a gamble .

Consider the consequence [ di , 0 ; ] for sure vs . the gamble where C occurs with

**probability**u and c occurs with**probability**1 - U . The diagram of fig . 1 describesthe situation . . C [ di , 0 ; ] ~ Fig . 1 . – [ di , 0 ; ] for sure equivalent to a gamble .

### What people are saying - Write a review

We haven't found any reviews in the usual places.

### Contents

STATISTICAL THEORY OF RELIABLITY | 8 |

Definitions and characterizations | 12 |

J KEILSON Stochastic models in reliability theory | 23 |

Copyright | |

37 other sections not shown

### Common terms and phrases

analysis application approach associated assume assumption BARLOW Bayesian calculation called complex components consider constant continuous correctness Course defined density depends derived described detected determine discussed distribution edited epochs equations equivalence ergodic errors estimate example exists expected exponential fact fail failure rate fault function given Hence important increasing independent input integration interest interval known likelihood limit Markov matrix mean measure method modules normal Note observed obtain occur operational parameters performance phase positive possible posterior predictive prior probability problem procedure prove random variables renewal repair requirements rule sample selected sequence simple software reliability space specification statistical stochastic structure Suppose task theorem theory tion transition tree University values York