Package: priorsense 1.0.3

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]

priorsense_1.0.3.tar.gz
priorsense_1.0.3.tar.gz(r-4.5-noble)priorsense_1.0.3.tar.gz(r-4.4-noble)
priorsense_1.0.3.tgz(r-4.4-emscripten)priorsense_1.0.3.tgz(r-4.3-emscripten)
priorsense.pdf |priorsense.html✨
priorsense/json (API)
NEWS

# Install 'priorsense' in R:

install.packages('priorsense', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

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

14 exports 4.16 score 41 dependencies 69 scripts 1.0k downloads

Last updated 3 days agofrom:a1a25e2518. Checks:OK: 2. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Oct 02 2024
R-4.5-linux	OK	Oct 02 2024

Exports:cjs_dist create_priorsense_data example_powerscale_model log_lik_draws log_prior_draws powerscale powerscale_derivative powerscale_gradients powerscale_plot_dens powerscale_plot_ecdf powerscale_plot_quantities powerscale_sensitivity powerscale_sequence predictions_as_draws

Dependencies:abind backports checkmate cli colorspace distributional fansi farver generics ggdist ggh4x ggplot2 glue gtable isoband labeling lattice lifecycle magrittr MASS Matrix matrixStats mgcv munsell nlme numDeriv pillar pkgconfig posterior quadprog R6 RColorBrewer Rcpp rlang scales tensorA tibble utf8 vctrs viridisLite withr

Power-scaling sensitivity analysis

Rendered frompowerscaling.Rmdusingknitr::rmarkdownon Oct 02 2024.

Last update: 2024-07-17
Started: 2024-06-21

Citation

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