Estimate Evidence using a Nested Sampling Run — calculate.ernest

Computes evidence and related quantities from a nested sampling run, optionally by simulating the volumes of each nested likelihood shell.

Usage

# S3 method for class 'ernest_run'
calculate(x, ndraws = 1000L, ...)

Arguments

x: [ernest_run]
Results from a nested sampling run.
ndraws: [integer(1)]
The number of log-volume sequences to simulate. If equal to zero, no simulations will be made, and a one draw vector of log-volumes are produced from the estimates contained in x.
...: These dots are for future extensions and must be empty.

Value

[tibble::tibble()] with class ernest_estimate.

The iterative estimates from the nested sampling run. Contains the following columns:

log_lik: [rvar] The log-likelihood of the model.
log_volume: [rvar] The log-volume of the prior space.
log_weight: [rvar] The log weights of the points in the live set.
log_evidence: [rvar] The log-evidence of the model.

If ndraws = 0, an additional column is included:

log_evidence_err: [rvar] The standard error of the log-evidence.

References

Higson, E., Handley, W., Hobson, M., & Lasenby, A. (2019). Nestcheck: Diagnostic Tests for Nested Sampling Calculations. Monthly Notices of the Royal Astronomical Society, 483(2), 2044–2056. doi:10.1093/mnras/sty3090

Examples

# Load an example run
data(example_run)

# View results as a tibble with `ndraws = 0`.
calculate(example_run, ndraws = 0)
#> Nested sampling uncertainty estimates:
#> # of Simulated Draws: 0
#> Log-volume: -17 ± NA
#> Log-evidence: -9.1 ± NA

# Generate 100 simulated log-volume values for each iteration.
calculate(example_run, ndraws = 100)
#> Nested sampling uncertainty estimates:
#> # of Simulated Draws: 100
#> Log-volume: -17 ± 1.3
#> Log-evidence: -9.1 ± 0.07