Package index • shinymrp

Running the Shiny app

run_app(): Run the Shiny Application

Workflow object and methods

mrp_workflow(): Create a new MRPWorkflow object

MRPWorkflow: MRPWorkflow objects

compare_models(): Compare models using LOO-CV

covar_hist(): Create geographic covariate distribution histogram

create_model(): Create a new MRPModel object

demo_bars(): Create demographic comparison bar plots

estimate_map(): Create a choropleth map of MRP estimates

estimate_plot(): Visualize estimates for demographic groups

link_acs(): Link sample data to ACS data

load_pstrat(): Load custom poststratification data

outcome_map(): Visualize raw outcome measure by geography

outcome_plot(): Create summary plots of the outcome measure

pp_check(): Perform posterior predictive check

preprocess(): Preprocess sample data

preprocessed_data(): Return preprocessed sample data

sample_size_map(): Create sample size map

Model object and methods

MRPModel: MRPModel objects

check_estimate_exists(): Check if poststratification has been performed

check_fit_exists(): Check if model has been fitted

diagnostics(): Return sampling diagnostics

fit(): Fit multilevel regression model using cmdstanr

formula(): Return model formula

log_lik(): Create inputs for leave-one-out cross-validation

metadata(): Return model metadata.

model_spec(): Return model specification

poststratify(): Run poststratification to generate population estimates

ppc(): Create input for posterior predictive check

save(): Save model object to file

stan_code(): Return model Stan code.

summary(): Return posterior summary table

Other functions

example_sample_data(): Return example data

example_pstrat_data(): Return example poststratification data

example_model(): Return example MRPModel object with estimation results.