Package: leafwax 0.2.7

leafwax: Bayesian Inversion of Leaf Wax Hydrogen Isotopes to Precipitation

Bayesian inversion of leaf wax hydrogen isotopes to reconstruct precipitation isotopes using hierarchical spatial models. Provides fourteen Bayesian models that vary in their use of spatial Gaussian processes and ancillary covariates (precipitation amount, plant functional type, C4 fraction). Models are pre-computed using 'Stan' and stored as posterior distributions, so prediction does not require 'Stan' to be installed. A 100-draw fixture ships with the package; full 1000-draw posteriors are downloaded from a versioned 'Zenodo' deposit on first use; see Bradley (2026) <doi:10.5281/zenodo.20085465>.

Authors:Alex Bradley [aut, cre]

leafwax_0.2.7.tar.gz
leafwax_0.2.7.zip(r-4.7)leafwax_0.2.7.zip(r-4.6)leafwax_0.2.7.zip(r-4.5)
leafwax_0.2.7.tgz(r-4.6-any)leafwax_0.2.7.tgz(r-4.5-any)
leafwax_0.2.7.tar.gz(r-4.7-any)leafwax_0.2.7.tar.gz(r-4.6-any)
leafwax_0.2.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
leafwax/json (API)
NEWS

# Install 'leafwax' in R:
install.packages('leafwax', repos = c('https://bradleylab.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bradleylab/leafwax/issues

Pkgdown/docs site:https://bradleylab.github.io

Datasets:

On CRAN:

Conda:

4.40 score 6 scripts 34 exports 1 dependencies

Last updated from:085737c97e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK134
source / vignettesOK201
linux-release-x86_64OK127
macos-release-arm64OK180
macos-oldrel-arm64OK214
windows-develOK127
windows-releaseOK101
windows-oldrelOK95
wasm-releaseOK99

Exports:assess_claimavailable_modelsbatch_predictcheck_data_cacheclear_download_cachecompare_modelscompute_vegetation_envelopedetect_changedetect_model_capabilitiesdownload_model_dataestimate_temporal_autocorrelationgenerate_fibonacci_sphereget_all_model_metadataget_cache_dirget_cache_infoget_data_pathget_data_urlget_model_infoget_model_parametersinvert_d2hinvert_d2Hinvert_d2H_ensembleleafwax_configleafwax_set_configlist_cached_modelslist_model_nameslist_modelsload_posteriorslocal_effective_slopepredict_d2h_precippredict_spatial_dual_gpselect_best_model_from_flagsvalidate_inputsvalidate_model_inputs

Dependencies:jsonlite

When can a leaf-wax record support a precipitation-isotope claim?

Rendered frompaleo-record-workflow.Rmdusingknitr::rmarkdownon Jun 16 2026.

Last update: 2026-06-01
Started: 2026-05-08

Readme and manuals

Help Manual

Help pageTopics
Assess a paleoclimate claim against the leaf-wax taxonomyassess_claim
Get available modelsavailable_models
Batch predict precipitation d2H for multiple sitesbatch_predict
Check if model data exists in cachecheck_data_cache
Clear download cacheclear_download_cache
Compare predictions across multiple modelscompare_models
Vegetation-only envelope for a paleo wax-isotope recordcompute_vegetation_envelope
Within-record d2H_precip change detectiondetect_change
Detect model capabilities from static v10 metadatadetect_model_capabilities
Download model data from GitHub releasesdownload_model_data
Estimate lag-1 temporal autocorrelationestimate_temporal_autocorrelation
Example leaf wax hydrogen isotope dataexample_data
Get all model metadataget_all_model_metadata
Get leafwax data cache directoryget_cache_dir
Get cache size informationget_cache_info
Get path to data fileget_data_path
Get data download URLsget_data_url
Get model infoget_model_info
Get model parametersget_model_parameters
Invert leaf wax d2H to precipitation d2Hinvert_d2H invert_d2h
Ensemble predictions across multiple modelsinvert_d2H_ensemble
Get leafwax configurationleafwax_config
Set leafwax configurationleafwax_set_config
List available models in cachelist_cached_models
List model nameslist_model_names
List available models with detailslist_models
Load posterior draws for a modelload_posteriors
Local effective slope at a paleo-reconstruction sitelocal_effective_slope
Predict precipitation d2H from leaf wax d2Hpredict_d2h_precip
Print method for leafwax_posteriorprint.leafwax_posterior
Select best model based on available dataselect_best_model_from_flags
Validate input data for inversionvalidate_inputs
Validate inputs for a specific modelvalidate_model_inputs