Package index • CausalQueries

All functions

CausalQueries: 'CausalQueries'

collapse_data() expand_data() make_data() make_events(): 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

inspect() grab(): 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

make_parameters() set_parameters() get_parameters(): Setting parameters

print(<causal_model>): Print a short summary for a causal model

print(<model_query>): Print a tightened summary of model queries

make_priors() set_priors() get_priors(): Setting priors

query_distribution(): Calculate query distribution

increasing() non_decreasing() decreasing() non_increasing() interacts() complements() substitutes() te(): Query helpers

query_model(): Generate estimands data frame

realise_outcomes(): Realise outcomes

set_confound(): Set confound

set_prior_distribution(): Add prior distribution draws

set_restrictions(): Restrict a model

summary(<causal_model>) print(<summary.causal_model>): Summarizing causal models

summary(<model_query>) print(<summary.model_query>): Summarizing model queries

update_model(): Fit causal model using 'stan'