sample_post_nor_ref_marg_Psi {BayesMultMeta} | R Documentation |

## Metropolis-Hastings algorithm for the normal distribution and the Berger and
Bernardo reference prior, where `\mathbf{\Psi}`

is generated from the marginal
posterior.

### Description

This function implements Metropolis-Hastings algorithm for drawing samples
from the posterior distribution of `\mathbf{\mu}`

and `\mathbf{\Psi}`

under the assumption of the normal distribution when the Berger and Bernardo
reference prior is employed. At each step, the algorithm starts with
generating a draw from the marginal distribution of `\mathbf{\Psi}`

.

### Usage

```
sample_post_nor_ref_marg_Psi(X, U, Np)
```

### Arguments

`X` |
A |

`U` |
A |

`Np` |
Length of the generated Markov chain. |

### Value

List with the generated samples from the joint posterior distribution
of `\mathbf{\mu}`

and `\mathbf{\Psi}`

, where the values of
`\mathbf{\Psi}`

are presented by using the vec operator.

[Package

*BayesMultMeta*version 0.1.1 Index]