SelectMinED | R Documentation |

Select MinED samples from `candidates`

by optimizing the generalized MinED criterion in Joseph et al. (2019).

SelectMinED(candidates, candlf, n, gamma=1, s=2)

`candidates` |
Candidate samples from the target distribution, which can be MC, QMC, or MCMC samples. |

`candlf` |
The log-unnormalized density function values corresponding to the |

`n` |
The required number of MinED samples. |

`gamma` |
The parameter in the anealled version of density function. Optional, default is “1”. |

`s` |
The parameter in generalized distance. Optional, default is “2”. |

This function select MinED samples from a given set of candidate samples. The function is used internally in the `mined`

function repeatedly for K times, where K is the number of annealing steps in the algorithm. Refer to Joseph et al., (2018) for more details.

The value returned from the function is a list containing the following components:

`points` |
The MinED samples selected from the |

`logf` |
The log-unnormalized density function values of the |

Dianpeng Wang <wdp@bit.edu.cn> and V. Roshan Joseph <roshan@gatech.edu>

Joseph, V. R., Wang, D., Gu, L., Lv, S., and Tuo, R. (2019). "Deterministic Sampling of Expensive Posteriors Using Minimum Energy Designs", *Technometrics*, 61, 297-308, arXiv:1712.08929, DOI:10.1080/00401706.2018.1552203.

`mined`

cand <- matrix(runif(10000, min = -4, max = 4), ncol = 1) candlf <- log(dnorm(cand)) res <- mined::SelectMinED(cand, as.vector(candlf), 150, 1.0, 2.0) print(res) par(mfrow=c(1,2)) hist(cand) hist(res$points)

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