## Proceedings of the International School of Physics "Enrico Fermi". |

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Results 1-3 of 66

Page 145

interest A, we regard (1.1) as a function of A and call (1.2) £(AK,...,ojn) = A»exp[-

A j><] the

parameter A, is not a probability density in the parameter. Hence the vertical bar

in L is ...

interest A, we regard (1.1) as a function of A and call (1.2) £(AK,...,ojn) = A»exp[-

A j><] the

**likelihood**junction. (The**likelihood**, although a function of theparameter A, is not a probability density in the parameter. Hence the vertical bar

in L is ...

Page 382

These lead us to question the appropriateness of the method of maximum

motivate our consideration of the Bayesian point of view. 2) In sect. 3, we first

present an ...

These lead us to question the appropriateness of the method of maximum

**likelihood**for estimating the parameters of software reliability models, andmotivate our consideration of the Bayesian point of view. 2) In sect. 3, we first

present an ...

Page 481

These procedures both generate a success

calibrated in the same manner as the PC scale. Of the holistic procedures, the PC

approach is preferred, although it has a correspondingly higher overhead in

terms of ...

These procedures both generate a success

**likelihood**scale which can becalibrated in the same manner as the PC scale. Of the holistic procedures, the PC

approach is preferred, although it has a correspondingly higher overhead in

terms of ...

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### Contents

System Eeliabujty | 3 |

Statistical Theory of Eeliablitt | 8 |

Definitions and characterizations | 12 |

Copyright | |

39 other sections not shown

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### Common terms and phrases

algorithm approach associated assume assumption Bayesian boundary points chain coherent system complex conjugate prior consider correctness defined denote detected discussed edited equations equivalence class ergodic errors example exponential distribution failure rate Fault Tree Analysis function gamma given human reliability IEEE Trans IFEA implementation increasing independent input domain integration interval likelihood Markov Markov chain matrix mean method modules monotone month2 N. D. Singpurwalla number of failures number of system NUMITEMS observed obtained operational output parameters phase Poisson Poisson process possible predictive prior distribution probability problem procedure Proschan R. E. Barlow random variables reliability growth models reliability theory renewal theory repair requirements sample sect sequence Software Eng software reliability software reliability models specification Stat statistical stochastic stochastic process subsection system failure system reliability techniques theorem tion tt tt values vector zero