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

### From inside the book

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Page 180

2 , 7 l 1 In what follows , we show that , for n < no , the producer ( consumer ) can

gain more protection when using the decision rule specified by ( 2 . 2 ) by

increasing n when F is IFR ( DFR ) .

for the ...

2 , 7 l 1 In what follows , we show that , for n < no , 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 boundariesfor the ...

Page 218

We also

{ F ; } is a filtration , or nondecreasing family of ( complete , right - continuous ) o -

algebras , F CFCF , Vs < t . Anyway , for each t , F , is the family of events whose ...

We also

**consider**a history , or flux of information { F } . A more formal definition of{ F ; } is a filtration , or nondecreasing family of ( complete , right - continuous ) o -

algebras , F CFCF , Vs < t . Anyway , for each t , F , is the family of events whose ...

Page 479

This is because the failure model only

overall HEPs from the constituent task element HEPs . ... This approach makes it

very diffiult to

This is because the failure model only

**considers**one route when synthesizing theoverall HEPs from the constituent task element HEPs . ... This approach makes it

very diffiult to

**consider**the probability of diagnostic and other errors . The data ...### What people are saying - Write a review

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### 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