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

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Results 1-3 of 59

Page 203

Ux > 0 under the IFR

DFR

distribution of the wi in order to represent informed opinion . This may be

accomplished by ...

Ux > 0 under the IFR

**assumption**and ( 3 . 4 ) 0 < U < U2 < . . . < Ux < 1 under theDFR

**assumption**. These restrictions must be reflected in the prior jointdistribution of the wi in order to represent informed opinion . This may be

accomplished by ...

Page 300

The major

selected randomly and independently from the input domain according to the

operational distribution . This is a very strong

general ...

The major

**assumption**of all software reliability growth models is : Inputs areselected randomly and independently from the input domain according to the

operational distribution . This is a very strong

**assumption**and will not hold ingeneral ...

Page 326

The major

Inputs are selected randomly and independently from the input domain according

to the operational distribution . This is a very strong

...

The major

**assumption**of all software reliability growth models is :**Assumption**.Inputs are selected randomly and independently from the input domain according

to the operational distribution . This is a very strong

**assumption**and will not hold...

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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