Skip to contents

Load posterior draws for a model

Source: R/load_posteriors.R
load_posteriors.Rd

Loads posterior draws for one of the 14 leafwax v10 models. The function searches three tiers in order:

Usage

load_posteriors(model_name, n_draws = NULL, verbose = TRUE)

Arguments

model_name

Character string specifying the model name.

n_draws

Integer number of posterior draws to use, or NULL for all available. Requesting more draws than are present silently returns whatever is available (e.g. all 100 from the preview tier).

verbose

Logical indicating whether to print loading info.

Value

A leafwax_posterior object: a list with draws, metadata (including metadata$tier, one of "heavy", "cache", "light"), optional spatial, and accessor closures.

Details

  1. Heavy posteriors at inst/extdata/posteriors/ (1000 draws, development install only; excluded from the CRAN tarball).

  2. Cache populated by download_model_data() under get_cache_dir().

  3. Preview posteriors at inst/extdata/posteriors_light/. These are a 100-draw stratified subsample shipped with every install so examples and tests run offline. They are intended as a fixture for code-path verification, not for inference: tail probabilities and 95% credible intervals are noisy at this sample size. The package issues a warning whenever the preview tier is in use; downstream functions (invert_d2H(), assess_claim(), detect_change()) repeat the warning so it is visible at the call that actually matters.

For inference, run download_model_data() once to populate the cache and then call load_posteriors() again – the cache tier wins over the preview tier and no further downloads are needed.

Examples

# Load a model (preview tier on a fresh install)
model <- load_posteriors("baseline")
#> Loading model: baseline
#>   Loaded 100 draws, 17 parameters
#> Warning: leafwax preview posteriors in use: 100 draws of 'baseline'. Tail probabilities and 95% credible intervals are unstable at this sample size; not suitable for inference. Run download_model_data("baseline") for the full posterior.
#>   Loaded standardization parameters (20 fields)

# Spatial model with limited draws
model_fast <- load_posteriors("baseline_sp", n_draws = 50)
#> Loading model: baseline_sp
#>   Loaded 100 draws, 271 parameters
#>   Subsampled to 50 draws (deterministic stratified)
#> Warning: leafwax preview posteriors in use: 50 draws of 'baseline_sp'. Tail probabilities and 95% credible intervals are unstable at this sample size; not suitable for inference. Run download_model_data("baseline_sp") for the full posterior.
#>   Loaded 125 spatial knots
#>   Loaded standardization parameters (20 fields)