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:Noa Kallioinen [aut, cre, cph], Topi Paananen [aut], Paul-Christian Bürkner [aut], Aki Vehtari [aut], Frank Weber [ctb]

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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'))

Peer review:

Bug tracker:https://github.com/n-kall/priorsense/issues

On CRAN:

bayesbayesianbayesian-data-analysisbayesian-methodsprior-distributionsensitivity-analysisstan

8.22 score 55 stars 65 scripts 1.7k downloads 14 exports 41 dependencies

Last updated 5 days agofrom:f31df102a9. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 01 2024
R-4.5-winNOTENov 01 2024
R-4.5-linuxNOTENov 01 2024
R-4.4-winNOTENov 01 2024
R-4.4-macNOTENov 01 2024
R-4.3-winNOTENov 01 2024
R-4.3-macNOTENov 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

Power-scaling sensitivity analysis

Rendered frompowerscaling.Rmdusingknitr::rmarkdownon Nov 01 2024.

Last update: 2024-07-16
Started: 2021-07-07

Readme and manuals

Help Manual

Help pageTopics
priorsense: Prior (and likelihood) diagnostics and sensitivity analysispriorsense-package priorsense
Cumulative Jensen-Shannon divergencecjs_dist
Create data structure for priorsensecreate-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-scalingexample_powerscale_model
Extract log likelihood drawslog_lik_draws log_lik_draws.CmdStanFit log_lik_draws.draws log_lik_draws.stanfit
Extract log prior drawslog_prior_draws log_prior_draws.CmdStanFit log_prior_draws.draws log_prior_draws.stanfit
Derivative with respect to power-scalingpowerscale_derivative
Diagnostic plots for power-scaling sensitivitypowerscale_plots powerscale_plot_dens powerscale_plot_ecdf powerscale_plot_ecdf.powerscaled_sequence powerscale_plot_quantities powerscale_plot_quantities.powerscaled_sequence
Power-scale gradientspowerscale-gradients powerscale_gradients powerscale_gradients.default powerscale_gradients.priorsense_data
Prior/likelihood power-scaling perturbationpowerscale powerscale-overview powerscale.default powerscale.priorsense_data powerscale_sequence powerscale_sequence.default powerscale_sequence.priorsense_data
Power-scaling sensitivity analysispowerscale-sensitivity powerscale_sensitivity powerscale_sensitivity.CmdStanFit powerscale_sensitivity.default powerscale_sensitivity.priorsense_data powerscale_sensitivity.stanfit
brms predictions as drawspredictions_as_draws