Generate a sample from a probability distribution with the covariance-matching slice sampling method.

1 2 | ```
cov.match.sample(target.dist, x0, sample.size, tuning=1,
theta=1, limit=length(x0)*100)
``` |

`target.dist` |
Target distribution; see |

`x0` |
Initial coordinates. |

`sample.size` |
Sample size to draw. |

`tuning` |
A tuning parameter; corresponds to |

`theta` |
A factor to scale the crumb standard deviation in
every direction after a proposal is rejected. So, after |

`limit` |
A limit on the number of log-density evaluations per observation before sampling is aborted. |

This function implements the covariance-matching 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`

, `grads`

, and
`adapt.rate`

. `adapt.rate`

indicates the fraction of
crumb draws that resulted in adaptation. This sampler follows
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`

,
`shrinking.rank.sample`

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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