Summarise posterior parameter distributions

Compute summary statistics (mean, median, confidence intervals) for posterior parameters from ABC results.

Usage

summarise_posterior_parameters(data, ...)

# S3 method for class 'abc'
summarise_posterior_parameters(data, ..., ci_level = 0.95)

Arguments

data

An abc object containing posterior samples in adj.values or unadj.values.

...

Additional arguments for custom summary functions. Functions passed as named arguments will be applied to each parameter's posterior samples.

ci_level

Numeric; confidence interval level (default: 0.95).

Value

A data frame with summary statistics for each parameter.

See also

summarise_posterior_parameters.abc

Examples

# Load ABC output from saved file
abc_file <- system.file(
  "extdata", "rdm_minimal", "abc", "abc_rejection_model.rds",
  package = "eam"
)
abc_rejection_model <- readRDS(abc_file)

# Summarise posterior distributions
summarise_posterior_parameters(abc_rejection_model)
#>      parameter      mean    median ci_lower_0.025 ci_upper_0.975
#> 1     V_beta_1 0.2684096 0.2607152      0.1119190      0.4470107
#> 2 V_beta_group 0.1949098 0.1879120      0.1036883      0.2958763

# Custom confidence interval level
summarise_posterior_parameters(abc_rejection_model, ci_level = 0.90)
#>      parameter      mean    median ci_lower_0.050 ci_upper_0.950
#> 1     V_beta_1 0.2684096 0.2607152      0.1291406       0.422611
#> 2 V_beta_group 0.1949098 0.1879120      0.1070319       0.290407