Man pages for CausalQueries
Make, Update, and Query Binary Causal Models
| add_dots | Helper to fill in missing do operators in causal expression |
| add_wildcard | Adds a wildcard for every missing parent |
| CausalQueries_internal_inherit_params | Create parameter documentation to inherit |
| CausalQueries-package | 'CausalQueries' |
| causal_type_names | Names for causal types |
| check_args | helper to check arguments |
| check_query | Warn about improper query specification and apply fixes |
| check_string_input | Check string_input |
| clean_condition | Clean condition |
| clean_params | Check parameters sum to 1 in param_set; normalize if needed;... |
| clean_param_vector | Clean parameter vector |
| collapse_data | Make compact data with data strategies |
| collapse_nodal_types | collapse nodal types |
| complements | Make statement for complements |
| construct_commands_alter_at | make_par_values |
| construct_commands_other_args | make_par_values |
| construct_commands_param_names | make_par_values |
| data_to_data | helper to generate a matrix mapping from names of M to names... |
| data_type_names | Data type names |
| decreasing | Make monotonicity statement (negative) |
| default_stan_control | default_stan_control |
| democracy_data | Development and Democratization: Data for replication of... |
| draw_causal_type | Draw a single causal type given a parameter vector |
| drop_empty_families | Drop empty families |
| expand_data | Expand compact data object to data frame |
| expand_nodal_expression | Helper to expand nodal expression |
| expand_wildcard | Expand wildcard |
| find_rounding_threshold | helper to find rounding thresholds for print methods |
| get_all_data_types | Get all data types |
| get_ambiguities_matrix | Get ambiguities matrix |
| get_causal_types | Get causal types |
| get_data_families | get_data_families |
| get_estimands | helper to get estimands |
| get_event_probabilities | Draw event probabilities |
| get_nodal_types | Get list of types for nodes in a DAG |
| get_param_dist | Get a distribution of model parameters |
| get_parameter_matrix | Get parameter matrix |
| get_parameter_names | Get parameter names |
| get_parents | Get list of parents of all nodes in a model |
| get_parmap | Get parmap: a matrix mapping from parameters to data types |
| get_posterior_distribution | Get the posterior distribution from a model |
| get_prior_distribution | Get a prior distribution from model |
| get_query_types | Look up query types |
| get_type_distributions | helper to get type distributions |
| get_type_names | Get type names |
| get_type_prob | Get type probabilities |
| get_type_prob_c | generates one draw from type probability distribution for... |
| get_type_prob_multiple | Draw matrix of type probabilities, before or after estimation |
| get_type_prob_multiple_c | generates n draws from type probability distribution for each... |
| grab | Grab |
| gsub_many | Recursive substitution |
| increasing | Make monotonicity statement (positive) |
| institutions_data | Institutions and growth: Data for replication of analysis in... |
| interacts | Make statement for any interaction |
| interpret_type | Interpret or find position in nodal type |
| is_a_model | Check whether argument is a model |
| lipids_data | Lipids: Data for Chickering and Pearl replication |
| list_non_parents | Returns a list with the nodes that are not directly pointing... |
| make_ambiguities_matrix | Make ambiguities matrix |
| make_data | Make data |
| make_data_single | Generate full dataset |
| make_events | Make data in compact form |
| make_model | Make a model |
| make_nodal_types | Make nodal types |
| make_parameter_matrix | Make parameter matrix |
| make_parameters_df | function to make a parameters_df from nodal types |
| make_parmap | Make parmap: a matrix mapping from parameters to data types |
| make_par_values | make_par_values |
| make_par_values_stops | make_par_values_stops |
| make_prior_distribution | Make a prior distribution from priors |
| minimal_data | Creates a data frame for case with no data |
| minimal_event_data | Creates a compact data frame for case with no data |
| n_check | n_check |
| nodes_in_statement | Identify nodes in a statement |
| non_decreasing | Make monotonicity statement (non negative) |
| non_increasing | Make monotonicity statement (non positive) |
| observe_data | Observe data, given a strategy |
| parameter_setting | Setting parameters |
| parents_to_int | Helper to turn parents_list into a list of data_realizations... |
| perm | Produces the possible permutations of a set of nodes |
| plot_model | Plots a DAG in ggplot style using a causal model input |
| prep_stan_data | Prepare data for 'stan' |
| print.causal_model | Print a short summary for a causal model |
| print.causal_types | Print a short summary for causal_model causal-types |
| print.dag | Print a short summary for a causal_model DAG |
| print.event_probabilities | Print a short summary for event probabilities |
| print.model_query | Print a tightened summary of model queries |
| print.nodal_types | Print a short summary for causal_model nodal-types |
| print.nodes | Print a short summary for causal_model nodes |
| print.parameter_mapping | Print a short summary for paramater mapping matrix |
| print.parameters | Print a short summary for causal_model parameters |
| print.parameters_df | Print a short summary for a causal_model parameters... |
| print.parameters_posterior | Print a short summary for causal_model parameter posterior... |
| print.parameters_prior | Print a short summary for causal_model parameter prior... |
| print.parents_df | Print a short summary for a causal_model parents data-frame |
| print.posterior_event_probabilities | Print a short summary of posterior_event_probabilities |
| print.stan_summary | Print a short summary for stan fit |
| print.statement | Print a short summary for a causal_model statement |
| print.type_distribution | Print a short summary for causal-type posterior distributions |
| print.type_prior | Print a short summary for causal-type prior distributions |
| prior_setting | Setting priors |
| queries_to_types | helper to get types from queries |
| query_distribution | Calculate query distribution |
| query_model | Generate estimands dataframe |
| query_to_expression | Helper to turn query into a data expression |
| realise_outcomes | Realise outcomes |
| restrict_by_labels | Reduce nodal types using labels |
| restrict_by_query | Reduce nodal types using statement |
| reveal_outcomes | Reveal outcomes |
| set_ambiguities_matrix | Set ambiguity matrix |
| set_confound | Set confound |
| set_parameter_matrix | Set parameter matrix |
| set_parmap | Set parmap: a matrix mapping from parameters to data types |
| set_prior_distribution | Add prior distribution draws |
| set_restrictions | Restrict a model |
| set_sampling_args | set_sampling_args From 'rstanarm' (November 1st, 2019) |
| simulate_data | simulate_data is an alias for make_data |
| st_within | Get string between two regular expression patterns |
| substitutes | Make statement for substitutes |
| summarise_distribution | helper to compute mean and sd of a distribution data.frame |
| summary.causal_model | Summarizing causal models |
| te | Make treatment effect statement (positive) |
| type_matrix | Generate type matrix |
| uncollapse_nodal_types | uncollapse nodal types |
| unpack_wildcard | Unpack a wild card |
| update_causal_types | Update causal types based on nodal types |
| update_model | Fit causal model using 'stan' |
