Package: makemyprior 1.2.2

Ingeborg Hem

makemyprior: Intuitive Construction of Joint Priors for Variance Parameters

Tool for easy prior construction and visualization. It helps to formulates joint prior distributions for variance parameters in latent Gaussian models. The resulting prior is robust and can be created in an intuitive way. A graphical user interface (GUI) can be used to choose the joint prior, where the user can click through the model and select priors. An extensive guide is available in the GUI. The package allows for direct inference with the specified model and prior. Using a hierarchical variance decomposition, we formulate a joint variance prior that takes the whole model structure into account. In this way, existing knowledge can intuitively be incorporated at the level it applies to. Alternatively, one can use independent variance priors for each model components in the latent Gaussian model. Details can be found in the accompanying scientific paper: Hem, Fuglstad, Riebler (2024, Journal of Statistical Software, <doi:10.18637/jss.v110.i03>).

Authors:Ingeborg Hem [cre, aut], Geir-Arne Fuglstad [aut], Andrea Riebler [aut]

makemyprior_1.2.2.tar.gz
makemyprior_1.2.2.zip(r-4.7)makemyprior_1.2.2.zip(r-4.6)makemyprior_1.2.2.zip(r-4.5)
makemyprior_1.2.2.tgz(r-4.6-any)makemyprior_1.2.2.tgz(r-4.5-any)
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makemyprior_1.2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
makemyprior/json (API)

# Install 'makemyprior' in R:
install.packages('makemyprior', repos = c('https://ingebogh.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ingebogh/makemyprior/issues

Datasets:

On CRAN:

Conda:

5.14 score 3 stars 23 scripts 298 downloads 30 exports 55 dependencies

Last updated from:ab64744f1e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK216
source / vignettesOK233
linux-release-x86_64OK217
macos-release-arm64OK155
macos-oldrel-arm64OK111
windows-develOK191
windows-releaseOK182
windows-oldrelOK168
wasm-releaseOK176

Exports:compile_stancreate_stan_fileeval_joint_prioreval_pc_priorexpitextract_posterior_effectextract_posterior_parameterfind_pc_prior_paramget_parameter_orderinference_inlainference_stanlogitmake_eval_prior_datamake_priormakemyprior_example_modelmakemyprior_guimakemyprior_modelsmakemyprior_plottingmcplot_marginal_priorplot_posterior_fixedplot_posterior_precisionplot_posterior_stanplot_posterior_stdevplot_posterior_varianceplot_priorplot_several_posterior_stanplot_tree_structurescale_precmattypical_variance

Dependencies:base64encbslibcachemclicommonmarkcpp11digestevaluatefarverfastmapfontawesomefsggplot2gluegtablehighrhtmltoolshtmlwidgetshttpuvisobandjquerylibjsonliteknitrlabelinglaterlatticelifecyclemagrittrMASSMatrixmemoisemimeotelpromisesR6rappdirsRColorBrewerRcpprlangrmarkdownS7sassscalesshinyshinyBSshinyjssourcetoolstinytexvctrsviridisLitevisNetworkwithrxfunxtableyaml

Latin square experiment
Model | Prior 1 | Prior 2 | Prior 3 | References

Last update: 2024-02-20
Started: 2021-05-18

Example i.i.d. model
Prior options | Model description | Make data and linear predictor | Make prior | Inference | Stan | INLA | Default settings | Additional examples | References

Last update: 2024-02-20
Started: 2021-05-18

Neonatal mortality
Model | Prior 1 | Prior 2 | References

Last update: 2024-02-20
Started: 2021-05-18

Wheat breeding
Model | Prior 1 | Prior 2 | References

Last update: 2023-11-07
Started: 2021-05-18

Readme and manuals

Help Manual

Help pageTopics
Compile stan-modelcompile_stan
Create a "skeleton" for custom Stan codecreate_stan_file
Evaluate the joint variance prioreval_joint_prior make_eval_prior_data
Evaluate PC prior for variance proportioneval_pc_prior
expitexpit
Extract the posterior of a random effectextract_posterior_effect
Extract the posterior parameter estimateextract_posterior_parameter
Find suitable PC prior parametersfind_pc_prior_param
Internal variance parameter orderget_parameter_order
Run inferenceinference_inla
Run inferenceinference_stan
Latin square experiment datalatin_data
logitlogit
Making a prior objectmake_prior
Returning a simple example prior objectmakemyprior_example_model
Graphical prior constructionmakemyprior_gui
List available priors, latent models and likelihoodsmakemyprior_models
List of available plotting functionsmakemyprior_plotting
Define latent componentmc
Neonatal mortality dataneonatal_data
Plotting prior for a single parameter (weight or variance (not standard deviation))plot_marginal_prior
Plotting posterior distributionsplot_posterior_fixed
Plotting posterior distributionsplot_posterior_stan
Plotting posterior variances, standard deviations or precisionsplot_posterior_precision plot_posterior_stdev plot_posterior_variance
Plotting prior distributionsplot_prior
Plotting several posterior distributionsplot_several_posterior_stan
Plotting the prior tree structure graphplot_tree_structure
Plottingplot.mmp_inla plot.mmp_prior plot.mmp_stan
Printprint.mmp_inla print.mmp_prior print.mmp_stan
Scaling precision matrixscale_precmat
Short summarysummary.mmp_inla summary.mmp_prior summary.mmp_stan
Compute the typical variancetypical_variance
Genomic wheat breeding model datawheat_data