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Prepare a new nested sampling run

Source: R/ernest_sampler.R
ernest_sampler.Rd

Initializes an ernest_sampler object containing the components required to perform nested sampling. This object can then be used to build sequences of nested samples with generate().

Usage

ernest_sampler(
  log_lik,
  prior,
  sampler = rwmh_cube(),
  nlive = 500,
  first_update = NULL,
  update_interval = NULL,
  seed = NA
)

Arguments

log_lik

[function] or [ernest_likelihood]
A function which computes the log-likelihood of a given model. If a function, it is wrapped with create_likelihood().

prior

[ernest_prior]
Describes the prior space within which to generate samples.

sampler

[ernest_lrps]
Specifies the likelihood-restricted prior sampling method used to replace points within the live set.

nlive

[integer(1)]
The number of points to generate within the live set. Strictly positive.

first_update

[integer(1)]
The number of likelihood calls to make with the default uniform LRPS method before swapping to the technique described by sampler. Optional; if left NULL this is set to nlive * 2.5.

update_interval

[integer(1)]
The number of likelihood calls between updates to the sampler object. Optional; if left NULL this is set to nlive * 1.5.

seed

[integer(1)]
Sets the random seed controlling the random number generator for nested sampling runs. Optional; if left NA the .Random.seed set within R is preserved and restored after a run.

Value

[ernest_sampler]
A named list, containing a specification for a nested sampling run. Contains the arguments passed to this function as well as an environment run_env, which is used to store the live set during sampling.

Details

The ernest_sampler object is tested with compile() before it is returned. This helps to catch errors with the likelihood and prior specifications. If this compilation step fails, review your log_lik_fn and prior objects for their compliance.

Verbosity

Messages from ernest can be silenced with the global options rlib_message_verbosity and rlib_warning_verbosity. These options take the values:

  • "default": Verbose unless the .frequency argument is supplied.

  • "verbose": Always verbose.

  • "quiet": Always quiet.

When set to quiet, messages are not displayed and the condition is not signaled. See rlang::abort() for more information.

Examples

prior <- create_uniform_prior(lower = c(-1, -1), upper = 1)
ll_fn <- function(x) -sum(x^2)
sampler <- ernest_sampler(ll_fn, prior, nlive = 100)
sampler
#> Nested sampling run specification:
#> * No. points: 100
#> * Sampling method: 25-step random walk sampling (acceptance target = 50.0%)
#> * Prior: uniform prior distribution with 2 dimensions (Uniform_1 and Uniform_2)

# Use a unit-cube LRPS (not recommended in practice)
unit_sampler <- ernest_sampler(
  ll_fn,
  prior,
  nlive = 100,
  sampler = unif_cube()
)
unit_sampler
#> Nested sampling run specification:
#> * No. points: 100
#> * Sampling method: Uniform unit cube sampling
#> * Prior: uniform prior distribution with 2 dimensions (Uniform_1 and Uniform_2)