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

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Page 25

A. Serra, Richard E. Barlow. one random variable stochastic process elementary

events 8 = { w } compound events A = { W : WE A } S = { wiw is a

function ] A = { W ; W E A } ( a bet on the

taking ...

A. Serra, Richard E. Barlow. one random variable stochastic process elementary

events 8 = { w } compound events A = { W : WE A } S = { wiw is a

**sequence**or afunction ] A = { W ; W E A } ( a bet on the

**sequence**w ) X . : 8 → ( X = ( w ) ) (taking ...

Page 117

Conditionally increasing in

We begin this section by confining attention to one - dimensional stochastic

processes . 5 ' 1 . Definition [ 11 ] . - Let { X ( t ) ; > 0 } be a real - valued Markov ...

Conditionally increasing in

**sequence**and time - associated random processes .We begin this section by confining attention to one - dimensional stochastic

processes . 5 ' 1 . Definition [ 11 ] . - Let { X ( t ) ; > 0 } be a real - valued Markov ...

Page 191

... the kernel is very important , and to a large extent determines the properties of

the estimators . WATSON and LEADBETTER [ 18 ] introduced a

functions { 8n ( x ) } which satisfies the following conditions : a ) On € L1 ( i . e .

518 .

... the kernel is very important , and to a large extent determines the properties of

the estimators . WATSON and LEADBETTER [ 18 ] introduced a

**sequence**offunctions { 8n ( x ) } which satisfies the following conditions : a ) On € L1 ( i . e .

518 .

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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