R: Bayesian Error Propagation and Forecast Uncertainty Decomposition

# Bayesian Error Propagation and Forecast Uncertainty Decomposition

## Documentation for package ‘ErrorTracer’ version 1.3.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

decompose_uncertainty | Extract or recompute uncertainty decomposition
et_calibrate | Assess calibration of posterior predictive intervals
et_diagnose | Diagnose a fitted ErrorTracer model
et_fit | Fit a Bayesian regression model with informed priors
et_pit | Probability integral transform (PIT) for calibration diagnostics
et_plot_calibration | Plot calibration: observed vs nominal coverage
et_plot_coefficients | Forest plot of regression coefficients
et_plot_decomposition | Plot uncertainty decomposition
et_plot_forecast | Plot posterior predictive fan chart
et_plot_pit | Plot a PIT / rank histogram for calibration
et_plot_prior_posterior | Plot prior vs posterior distributions for model coefficients
et_plot_sensitivity | Plot a sensitivity profile
et_plot_shelf_life | Plot forecast shelf life
et_predict | Posterior prediction with uncertainty decomposition
et_sensitivity_profile | Sensitivity profile of the environmental uncertainty component
et_sim | Simulated allele-frequency-change dataset for ErrorTracer tutorials
et_skill_score | Null-model-relative forecast skill (CRPS)
et_sobol | Global (Sobol) variance-based sensitivity of the predictive mean
et_theme | Minimal ggplot2 theme for ErrorTracer plots
extract_priors | Extract brms prior specification from a regularized or standard regression model
extract_priors.cv.glmnet | Extract brms prior specification from a regularized or standard regression model
extract_priors.glm | Extract brms prior specification from a regularized or standard regression model
extract_priors.glmnet | Extract brms prior specification from a regularized or standard regression model
extract_priors.lm | Extract brms prior specification from a regularized or standard regression model
extract_priors.ranger | Extract brms prior specification from a regularized or standard regression model
shelf_life | Compute the forecast shelf life
standardize | Standardize a numeric vector (mean-centre, unit-variance)
unstandardize | Reverse standardization