Package: priorsense 1.0.4
Noa Kallioinen
priorsense: Prior Diagnostics and Sensitivity Analysis
Provides functions for prior and likelihood sensitivity analysis in Bayesian models. Currently it implements methods to determine the sensitivity of the posterior to power-scaling perturbations of the prior and likelihood.
Authors:
priorsense_1.0.4.tar.gz
priorsense_1.0.4.zip(r-4.5)priorsense_1.0.4.zip(r-4.4)priorsense_1.0.4.zip(r-4.3)
priorsense_1.0.4.tgz(r-4.4-any)priorsense_1.0.4.tgz(r-4.3-any)
priorsense_1.0.4.tar.gz(r-4.5-noble)priorsense_1.0.4.tar.gz(r-4.4-noble)
priorsense_1.0.4.tgz(r-4.4-emscripten)priorsense_1.0.4.tgz(r-4.3-emscripten)
priorsense.pdf |priorsense.html✨
priorsense/json (API)
NEWS
# Install 'priorsense' in R: |
install.packages('priorsense', repos = c('https://n-kall.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/n-kall/priorsense/issues
bayesbayesianbayesian-data-analysisbayesian-methodsprior-distributionsensitivity-analysisstan
Last updated 5 days agofrom:f31df102a9. Checks:OK: 1 NOTE: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 01 2024 |
R-4.5-win | NOTE | Nov 01 2024 |
R-4.5-linux | NOTE | Nov 01 2024 |
R-4.4-win | NOTE | Nov 01 2024 |
R-4.4-mac | NOTE | Nov 01 2024 |
R-4.3-win | NOTE | Nov 01 2024 |
R-4.3-mac | NOTE | Nov 01 2024 |
Exports:cjs_distcreate_priorsense_dataexample_powerscale_modellog_lik_drawslog_prior_drawspowerscalepowerscale_derivativepowerscale_gradientspowerscale_plot_denspowerscale_plot_ecdfpowerscale_plot_quantitiespowerscale_sensitivitypowerscale_sequencepredictions_as_draws
Dependencies:abindbackportscheckmateclicolorspacedistributionalfansifarvergenericsggdistggh4xggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivpillarpkgconfigposteriorquadprogR6RColorBrewerRcpprlangscalestensorAtibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
priorsense: Prior (and likelihood) diagnostics and sensitivity analysis | priorsense-package priorsense |
Cumulative Jensen-Shannon divergence | cjs_dist |
Create data structure for priorsense | create-priorsense-data create_priorsense_data create_priorsense_data.CmdStanFit create_priorsense_data.default create_priorsense_data.draws create_priorsense_data.stanfit |
Example Stan model for power-scaling | example_powerscale_model |
Extract log likelihood draws | log_lik_draws log_lik_draws.CmdStanFit log_lik_draws.draws log_lik_draws.stanfit |
Extract log prior draws | log_prior_draws log_prior_draws.CmdStanFit log_prior_draws.draws log_prior_draws.stanfit |
Derivative with respect to power-scaling | powerscale_derivative |
Diagnostic plots for power-scaling sensitivity | powerscale_plots powerscale_plot_dens powerscale_plot_ecdf powerscale_plot_ecdf.powerscaled_sequence powerscale_plot_quantities powerscale_plot_quantities.powerscaled_sequence |
Power-scale gradients | powerscale-gradients powerscale_gradients powerscale_gradients.default powerscale_gradients.priorsense_data |
Prior/likelihood power-scaling perturbation | powerscale powerscale-overview powerscale.default powerscale.priorsense_data powerscale_sequence powerscale_sequence.default powerscale_sequence.priorsense_data |
Power-scaling sensitivity analysis | powerscale-sensitivity powerscale_sensitivity powerscale_sensitivity.CmdStanFit powerscale_sensitivity.default powerscale_sensitivity.priorsense_data powerscale_sensitivity.stanfit |
brms predictions as draws | predictions_as_draws |