convolution.m | Computes (exactly) the probability that a sum of independent exponentially-distributed random variables, each with a distinct parameter, exceeds a given threshold. |

expt.m | Returns samples from a truncated exponential distribution. |

f_bar.m | Samples from the conditional density of repair times, given that at least one edge in every path in the path set is not operational at time 1. Uses path_sampling.m. |

hetero_PMC.m | Estimates the reliability of a certain network via permutation Monte Carlo. Uses S.m and convolution.m. |

IS_bounds.m | Estimates the reliability of a network using importance sampling with bounds. Uses f_bar.m, path_sampling.m, and S.m. |

leap_evolve.m | Estimates the reliability of a certain network via the leap-evolve algorithm. Uses S.m and convolution.m |

merge.m | Applies the merge algorithm of Elperin et al. (1991). Is used in merge_process.m. |

merge_process.m | Estimates the reliability of a certain network via the merge algorithm. Uses merge.m. |

path_sampling.m | Samples repair times from a set of paths. Uses expt.m. |

relbty_marginals (folder) | Estimates the reliability of a network using Markov chain Monte Carlo and the splitting method. |

S.m | Computes the time at which a network becomes operational (first and last nodes connected) given the times of repair. |

using_Sx.m | Illustrates how to use S.m for a certain graph. Uses S.m. |

back