proposals {pomp} | R Documentation |

## MCMC proposal distributions

### Description

Functions to construct proposal distributions for use with MCMC methods.

### Usage

```
mvn_diag_rw(rw.sd)
mvn_rw(rw.var)
mvn_rw_adaptive(
rw.sd,
rw.var,
scale.start = NA,
scale.cooling = 0.999,
shape.start = NA,
target = 0.234,
max.scaling = 50
)
```

### Arguments

`rw.sd` |
named numeric vector; random-walk SDs for a multivariate normal random-walk proposal with diagonal variance-covariance matrix. |

`rw.var` |
square numeric matrix with row- and column-names. Specifies the variance-covariance matrix for a multivariate normal random-walk proposal distribution. |

`scale.start` , `scale.cooling` , `shape.start` , `target` , `max.scaling` |
parameters
to control the proposal adaptation algorithm. Beginning with MCMC
iteration |

### Value

Each of these calls constructs a function suitable for use as the
`proposal`

argument of `pmcmc`

or `abc`

. Given a parameter
vector, each such function returns a single draw from the corresponding
proposal distribution.

### Author(s)

Aaron A. King, Sebastian Funk

### References

G.O. Roberts and J.S. Rosenthal. Examples of adaptive MCMC. *Journal of Computational and Graphical Statistics* **18**, 349–367, 2009. doi:10.1198/jcgs.2009.06134.

### See Also

More on Markov chain Monte Carlo methods:
`abc()`

,
`pmcmc()`

*pomp*version 5.11.0.0 Index]