ErrorTracer
1.2.1Bayesian Error Propagation and Forecast Uncertainty Decomposition
Overview
Provides a full pipeline from regularized or standard regression models (elastic net, linear models, generalized linear models, random forests) to informed Bayesian priors, structured forecast uncertainty decomposition (parameter / environmental / residual, plus a temporal component when the model carries an autocorrelation term), and forecast shelf life analysis (the quantification of when a forecast becomes uninformative). Designed for ecological and genomic forecasting with climate or environmental covariates. Methods build on Bürkner (2017) doi:10.18637/jss.v080.i01 for Bayesian regression via 'Stan', Friedman, Hastie, and Tibshirani (2010) doi:10.18637/jss.v033.i01 for elastic net regularization, Wright and Ziegler (2017) doi:10.18637/jss.v077.i01 for random forests, and Vehtari, Gelman, and Gabry (2017) doi:10.1007/s11222-016-9696-4 for leave-one-out cross-validation.
Install
Health
- OK2026-07-207 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-05-2611 OK · 0 NOTE · 0 WARNING · 2 ERROR · 0 FAILURE
- OK2026-05-057 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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People & History
3 releases. R releases are shown for context.
- 1.2.1Latest
- unarchivedReturned to CRAN2026-07-19
- archivedRemoved from CRAN2026-06-08issues were not corrected in time
- 1.1.02026-05-25 · diff ↗
- 1.0.22026-05-04
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-05-04
- Total releases
- 3 / 1 yrs
- License
- MIT + file LICENSE OSI
- Download size
- not tracked yet
- Installed size
- not tracked yet
- With dependencies
- not tracked yet