View source: R/debiasing_algorithm.R

Sample two MCMC chains, each following `single_kernel`

marginally,
and `coupled_kernel`

jointly, until min(max(tau, m), max_iterations), where tau
is the first time at which the two chains meet (i.e. take the same value exactly).
Or more precisely, they meet with a delay of one, i.e. X_t = Y_t-1. The chains
are initialized from the distribution provided in `rinit`

.

See `get_hmc_kernel`

for an example of function returning the appropriate kernels.

1 2 | ```
unbiased_estimator(single_kernel, coupled_kernel, rinit, h = function(x)
x, k = 0, m = 1, max_iterations = Inf)
``` |

`single_kernel` |
function taking a state (in a vector), its log density and an iteration, and returning
a list with a key named |

`coupled_kernel` |
function taking two states (in two vectors), their log densities and an iteration,
and returning a list with keys |

`rinit` |
function taking no arguments are returning an initial state for a Markov chain. |

`h` |
test function (possibly vector-valued) |

`k` |
burn-in parameter (default to 0) |

`m` |
time average parameter (will be proportional to the computing cost if meeting occurs before |

`max_iterations` |
number of iterations at which the function stops if it is still running (default to Inf). |

`logtarget` |
function evaluating the log target density |

pierrejacob/unbiasedpathsampling documentation built on May 17, 2019, 12:03 p.m.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.