Description Usage Arguments Details Value References See Also

Generate a sample from a probability distribution with the nonadaptive-crumb slice sampling method.

1 2 | ```
nonadaptive.crumb.sample(target.dist, x0, sample.size,
tuning=1, downscale=0.95)
``` |

`target.dist` |
Target distribution; see |

`x0` |
Numeric vector containing initial state. |

`sample.size` |
Requested sample size. |

`tuning` |
Initial crumb standard deviation. |

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

This function implements slice sampling with nonadaptive crumbs.
Crumbs are Gaussian with spherical covariance starting at
`tuning`

, decreasing by `downscale`

each time a proposal
is rejected. More information can be found in sec. 5.2 of Neal
(2003). This function 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`

.

Neal, Radford M. (2003), “Slice Sampling,” The Annals of Statistics 31(3):705-767.

`shrinking.rank.sample`

,
`compare.samplers`

SamplerCompare documentation built on Sept. 10, 2018, 5:05 p.m.

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