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

### From inside the book

Results 1-3 of 53

Page 160

A. Serra, Richard E. Barlow. is decreasing ( * ) in k > 0 for fixed T and increasing (

* ) in T for fixed k , i . e . the

decreasing in k and stochastically increasing in T . In particular , E [ / / k = 0 , T ] >

ELĠ \ k ...

A. Serra, Richard E. Barlow. is decreasing ( * ) in k > 0 for fixed T and increasing (

* ) in T for fixed k , i . e . the

**posterior**random variable ő is stochasticallydecreasing in k and stochastically increasing in T . In particular , E [ / / k = 0 , T ] >

ELĠ \ k ...

Page 161

1 , we plot the

coefficient of variation as a function of t , the test time elapsed . Table 3 . I may be

used to generate the plots . Note that failures cause vertical drops in the graphs .

In fig .

1 , we plot the

**posterior**mean ,**posterior**standard deviation and**posterior**coefficient of variation as a function of t , the test time elapsed . Table 3 . I may be

used to generate the plots . Note that failures cause vertical drops in the graphs .

In fig .

Page 205

It is also interesting to note that the Cov ( Ui , U ; ) is a function of both i and j ,

which takes into account the relative closeness of the intervals . Similar results

may be obtained for the DFR assumption . 4 . -

a ...

It is also interesting to note that the Cov ( Ui , U ; ) is a function of both i and j ,

which takes into account the relative closeness of the intervals . Similar results

may be obtained for the DFR assumption . 4 . -

**Posterior**analysis . If we assumea ...

### What people are saying - Write a review

We haven't found any reviews in the usual places.

### 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