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

### From inside the book

Results 1-3 of 52

Page 45

Let r ( t ) be the p . d . f . of the i . i . d .

( T ) = yri ( T ) + ( 1 - 7 ) r ( t ) , where y is the probability that the state 0 is not

visited during the

that 0 ...

Let r ( t ) be the p . d . f . of the i . i . d .

**intervals**between renewals , then ( 4 . 12 ) r( T ) = yri ( T ) + ( 1 - 7 ) r ( t ) , where y is the probability that the state 0 is not

visited during the

**interval**, ri ( t ) is the conditional p . d . f . for the**interval**giventhat 0 ...

Page 186

Suppose that the domain of r , [ 0 , 00 ) , is divided into k

42 ) , . . . , [ ( x - 1 , 00 ) . Let the j - th time

1 , with do = 0 , Ox = 00 . Let n ; be the number of _ X ; ' s which fall in 1 ; , j = 1 ...

Suppose that the domain of r , [ 0 , 00 ) , is divided into k

**intervals**[ 0 , 0 ) , [ Q1 ,42 ) , . . . , [ ( x - 1 , 00 ) . Let the j - th time

**interval**Ij , j = 1 , . . . , k , be 1 ; = ; — As -1 , with do = 0 , Ox = 00 . Let n ; be the number of _ X ; ' s which fall in 1 ; , j = 1 ...

Page 429

Note that a Duane growth curve ( see below ) has some technical difficulty in the

first

of models , as when retrofitting engineering changes gives less improvement ...

Note that a Duane growth curve ( see below ) has some technical difficulty in the

first

**interval**of model II . One can easily imagine combinations of these two typesof models , as when retrofitting engineering changes gives less improvement ...

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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