Description Usage Arguments Details Value Author(s) References Examples

Returns a list of all control parameters needed for univariate samplers. Parameter names (after removing the prefixes) are identical to those used in original packages / source code. To be used with multivariate distributions, all control parameters must have the same length as the dimensionality of state space, either as vectors or lists.

1 2 3 4 |

`n` |
Dimensionality of state space, corresponding to |

`slice.w` |
Size of the steps for creating slice sampler interval. |

`slice.m` |
Limit on stepout steps. |

`slice.lower` |
Lower bound on support of the distribution. |

`slice.upper` |
Upper bound on support of the distribution. |

`ars.x` |
A vector of starting points for each coordinate, over which log-density is defined. |

`ars.ns` |
Maximum number of points defining the hulls. |

`ars.m` |
Number of starting points. |

`ars.emax` |
Large value for which it is possible to compute an exponential. |

`ars.lb` |
Boolean indicating if there is a lower bound to the domain. |

`ars.xlb` |
Value of the lower bound. |

`ars.ub` |
Boolean indicating if there is an upper bound to the domain. |

`ars.xub` |
Value of the upper bound. |

`arms.indFunc` |
Indicator function of the convex support of the target density. |

`unimet.sigma` |
Standard deviation of Gaussian proposal. |

All arguments (aside from `n`

) supplied to `MfU.Control`

can be vectors (or in the case of `ars.x`

a list) of length `n`

, in which case they are kept unmodified. Alternatively, a single parameter can be passed into `MfU.Control`

, which is then expanded by the function into a vector/list of length `n`

by simple replication. Each element of the resulting vector/list is used for one of the `n`

visited coordinates during the univariate sampling cycles. Naming and description of arguments for each univariare sampler is kept in maximal consistency with original source codes / libraries.

A list with 4 elements, `slice`

, `ars`

, `arms`

, and `unimet`

, each containing elements of the same name as their corresponding arguments in the function call.

Alireza S. Mahani, Mansour T.A. Sharabiani

Gilks WR and Wild P (1992). Adaptive Rejection Sampling. *Applied Statistics*, **41**, 337-348.

Gilks WR, Best NG, and Tan KKC (1995). Adaptive rejection Metropolis sampling within Gibbs sampling. *Applied Statistics*, **44**, 455-472.

Mahani A.S and Sharabiani M.T.A. (2017). Multivariate-From-Univariate MCMC Sampler: The R Package MfUSampler. Journal of Statistical Software, Code Snippets, 78(1), 1-22. doi:10.18637/jss.v078.c01

Neal R.M. (2003). Slice Sampling. *Annals of Statistics*, **31**, 705-767.

1 2 3 4 | ```
# default control a for 10-dimensional space
mycontrol <- MfU.Control(10)
# setting a lower bound of 0 for last coordinate
mycontrol <- MfU.Control(10, slice.lower=c(rep(-Inf,9),0.0))
``` |

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