Description Usage Arguments Value Author(s) Examples

Implements a Metropolis-within-Gibbs sampling algorithm for an arbitrary real-valued posterior density defined by the user

1 |

`logpost` |
function defining the log posterior density |

`start` |
array with a single row that gives the starting value of the parameter vector |

`m` |
the number of iterations of the chain |

`scale` |
vector of scale parameters for the random walk Metropolis steps |

`...` |
data that is used in the function logpost |

`par` |
a matrix of simulated values where each row corresponds to a value of the vector parameter |

`accept` |
vector of acceptance rates of the Metropolis steps of the algorithm |

Jim Albert

1 2 3 4 5 |

```
```

LearnBayes documentation built on March 19, 2018, 1:04 a.m.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.