CausalQueries-package   CausalQueries: Make, Update, and Query Binary
                        Causal Models
data_helpers            Data helpers
democracy_data          Development and Democratization: Data for
                        replication of analysis in *Integrated
                        Inferences*
draw_causal_type        Draw a single causal type given a parameter
                        vector
get_all_data_types      Get all data types
get_event_probabilities
                        Draw event probabilities
get_query_types         Look up query types
inspection              Helpers for inspecting causal models
institutions_data       Institutions and growth: Data for replication
                        of analysis in *Integrated Inferences*
interpret_type          Interpret or find position in nodal type
lipids_data             Lipids: Data for Chickering and Pearl
                        replication
make_model              Make a model
parameter_setting       Setting parameters
print.causal_model      Print a short summary for a causal model
print.model_query       Print a tightened summary of model queries
prior_setting           Setting priors
query_distribution      Calculate query distribution
query_helpers           Query helpers
query_model             Generate data frame for batches of causal
                        queries
realise_outcomes        Realise outcomes
set_confound            Set confound
set_prior_distribution
                        Add prior distribution draws
set_restrictions        Restrict a model
summary.causal_model    Summarizing causal models
summary.model_query     Summarizing model queries
update_model            Fit causal model using 'stan'
