Skip to contents

Compile the live set of points for nested sampling

Source: R/compile.R
compile-ernest.Rd

Prepares an object for nested sampling by validating and (re)generating its live set. This ensures the sampler is viable before new points are drawn during the nested sampling algorithm.

Usage

# S3 method for class 'ernest_sampler'
compile(object, ...)

# S3 method for class 'ernest_run'
compile(object, clear = FALSE, ...)

Arguments

object

[ernest_run] or [ernest_sampler]
Results from a nested sampling run.

...

These dots are for future extensions and must be empty.

clear

[logical(1)]
If TRUE, clears results from previous runs before compiling. If FALSE, retains previous results and validates the live set.

Value

A copy of [object].

The copy is guaranteed to have a valid live set, created according to the class of object and the value of clear:

  • If object is an ernest_sampler, or if clear = TRUE, a new live set is created from scratch.

  • If object is an ernest_run, the live set is regenerated from previous results.

Details

compile() validates the live set bound to object, ensuring that:

  • Each point in the set is within the unit hypercube.

  • The likelihood function returns valid values (finite double or -Inf) for each point.

  • The live set does not represent a perfect likelihood plateau (i.e., that all points share the same likelihood). A warning is issued if more than 25% of points share the same likelihood value.

If validation fails, the live set is removed from object, preventing further sampling until the issue is resolved.

See also

generate.ernest_run()

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)

# Compile the sampler to add a live set
compile(sampler)
#> Nested sampling run specification:
#> * No. points: 100
#> * Sampling method: 25-step random walk sampling (acceptance target = 50%)
#> * Prior: uniform prior distribution with 2 dimensions (Uniform_1 and Uniform_2)
head(sampler$live_env$unit)
#>            [,1]      [,2]
#> [1,] 0.21405726 0.6334646
#> [2,] 0.35994692 0.9519752
#> [3,] 0.23487837 0.9404726
#> [4,] 0.04619817 0.7970183
#> [5,] 0.18004066 0.3764556
#> [6,] 0.21099128 0.6172439

# Continue a previous run
# run <- data(example_run)
# sampler_2 <- compile(example_run)
# sampler_2

# Make a new sampler from a previous run
sampler_3 <- compile(example_run, clear = TRUE)
sampler_3
#> Nested sampling run specification:
#> * No. points: 1000
#> * Sampling method: 25-step random walk sampling (acceptance target = 50%)
#> * Prior: uniform prior distribution with 3 dimensions (x, y, and z)