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

### From inside the book

Results 1-3 of 93

Page 16

It is easy to verify that the convolution of DFR

, simply convolve a gamma

, with itself . The convolution is a gamma

It is easy to verify that the convolution of DFR

**distributions**is not DFR . To see this, simply convolve a gamma

**distribution**of order a ( ? < « < 1 ) , a DFR**distribution**, with itself . The convolution is a gamma

**distribution**of order 2ų ( 20 > 1 ) , a ...Page 137

If we wish to know the

given by the multiple integral P ( S ) = . . . . Jo ( s – { x : ) fa ( ty ) . . . fxlxx ) d . cy . . .

day = dk exp liks f ( x ) exp [ - ikx , ] . . . fn ( xp ) exp ( - ikxx ] dx , . . . dxn = = dk ...

If we wish to know the

**distribution**function of S , the sum of the Xi , it is obviouslygiven by the multiple integral P ( S ) = . . . . Jo ( s – { x : ) fa ( ty ) . . . fxlxx ) d . cy . . .

day = dk exp liks f ( x ) exp [ - ikx , ] . . . fn ( xp ) exp ( - ikxx ] dx , . . . dxn = = dk ...

Page 203

These restrictions must be reflected in the prior joint

to represent informed opinion . This may be accomplished by using a Dirichlet

These restrictions must be reflected in the prior joint

**distribution**of the wi in orderto represent informed opinion . This may be accomplished by using a Dirichlet

**distribution**as the prior joint**distribution**for the random variables 14 ; — U9 , U ...### 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