Description Usage Arguments Examples

Simulates realisations from the posterior distribution for the index and shape parameters in a gamma distribution based on a random sample and independent gamma priors by using a Metropolis within Gibbs algorithm and a normal random walk proposal for the index parameter

1 2 |

`N` |
length of MCMC chain |

`initial` |
starting value for the algorithm |

`innov` |
standard deviation of normal random walk innovation for index parameter |

`priorparam` |
prior parameters a,b,c,d |

`n` |
size of random sample |

`xbar` |
(arithmetic) mean of random sample |

`xgbar` |
geometric mean of random sample |

`show` |
logical. If true then acceptance rate for the proposals will be given |

1 | ```
mcmcAnalysis(mwgGamma(100,(0.62/0.4)^2,0.8,c(2,1,3,1),50,0.62,0.46),rows=2)
``` |

mas3321 documentation built on May 31, 2017, 1:50 a.m.

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