Description Usage Arguments Details Value References See Also

Generate a sample from a probability distribution with the shrinking-rank slice sampling method.

1 2 | ```
shrinking.rank.sample(target.dist, x0, sample.size, tuning=1,
downscale=0.95, min.dimension=1)
``` |

`target.dist` |
Target distribution; see |

`x0` |
Numeric vector containing initial state. |

`sample.size` |
Requested sample size. |

`tuning` |
A tuning parameter; corresponds to |

`downscale` |
Factor to reduce crumb standard deviation by when a proposal is rejected. |

`min.dimension` |
The minimum dimension to sample crumbs from. |

`shrinking.rank.slice.sample`

implements the shrinking-rank
method of slice sampling, as described by Thompson and Neal (2010). It
can be passed to `compare.samplers`

in the `samplers`

list argument.

A list with elements `X`

, `evals`

, and `grads`

,
following the calling convention of `compare.samplers`

.

Thompson, M. B. and Neal, R. M. (2010). Covariance-adaptive slice sampling. Technical Report TR-1002, Dept. of Statistics, University of Toronto.

`compare.samplers`

`cov.match.sample`

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