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

### From inside the book

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Page 37

Since the

since v is arbitrary when large enough . ... In chains having infinite state spaces ,

irreducibility does not assure

Since the

**ergodic**vector of p ( t ) is unique , e " is independent of v as it should besince v is arbitrary when large enough . ... In chains having infinite state spaces ,

irreducibility does not assure

**ergodicity**because there is the possibility of ...Page 38

For an

the set of good ( working ) states of the system . Of equal accessibility to the

and n ...

For an

**ergodic**chain model , the availability A is given by A = Eem , where G isthe set of good ( working ) states of the system . Of equal accessibility to the

**ergodic**probabilities em is the steady - state flow rate imn between two states mand n ...

Page 42

In the same setting the

from a point chosen at random on the ...

relation to the sojourn time density as the residual lifetime at

In the same setting the

**ergodic**exit time is the time until the next departure from Gfrom a point chosen at random on the ...

**ergodic**exit time density bears the samerelation to the sojourn time density as the residual lifetime at

**ergodicity**bears to ...### 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