posterior.predictive.nl {BMAmevt} | R Documentation |

## Posterior predictive densities in the three dimensional PB, NL and NL3 models

### Description

Wrappers for `posterior.predictive3D`

in the PB and NL models.

### Usage

```
posterior.predictive.nl(
post.sample,
from = post.sample$Nbin + 1,
to = post.sample$Nsim,
thin = 50,
npoints = 40,
eps = 0.001,
equi = T,
displ = T,
...
)
posterior.predictive.pb(
post.sample,
from = post.sample$Nbin + 1,
to = post.sample$Nsim,
thin = 50,
npoints = 40,
eps = 10^(-3),
equi = T,
displ = T,
...
)
```

### Arguments

`post.sample` |
A posterior sample as returned by |

`from` |
Integer or |

`to` |
Integer or |

`thin` |
Thinning interval. |

`npoints` |
The number of grid nodes on the squared grid containing the desired triangle. |

`eps` |
Positive number: minimum distance from any node inside the simplex to the simplex boundary |

`equi` |
logical. Is the simplex represented as an equilateral triangle (if |

`displ` |
logical. Should a plot be produced ? |

`...` |
Additional graphical parameters and arguments to be passed
to |

### Details

The posterior predictive density is approximated by averaging the densities corresponding to the parameters stored in `post.sample`

. See
`posterior.predictive3D`

for details.

### Value

A `npoints*npoints`

matrix: the posterior predictive density.

### See Also

`posterior.predictive3D`

, `posteriorMCMC.pb`

.

*BMAmevt*version 1.0.5 Index]