# An Interface to Specify Causal Graphs and Compute Bounds on Causal Effects

## Documentation for package ‘causaloptim’ version 1.0.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

causaloptim-package | An Interface to Specify Causal Graphs and Compute Bounds on Causal Effects
analyze_graph | Analyze the causal graph and effect to determine constraints and objective
btm_var | Recursive function to get the last name in a list
causaloptim | An Interface to Specify Causal Graphs and Compute Bounds on Causal Effects
causalproblemcheck | Check conditions on causal problem
check_constraints_violated | Check whether any of the observable constraints implied by the causal model are violated for a given distribution of observables
check_linear_objective | Check linearity of objective function implied by a causal model and effect
check_parents | Check for paths from from to to
constraintscheck | Check constraints
create_causalmodel | Create a structural causal model from a graph or a set of response functions
create_effect_vector | Translate target effect to vector of response variables
create_linearcausalproblem | Create linear causal problem from causal model and effect
create_q_matrix | Translate response functions into matrix of counterfactuals
create_response_function | Translate regular DAG to response functions
find_all_paths | Find all paths in a causal model
get_default_effect | Define default effect for a given graph
graphrescheck | Check conditions on digraph
initialize_graph | Initialize an igraph object for use with causaloptim
interpret_bounds | Convert bounds string to a function
latex_bounds | Latex bounds equations
list_to_path | Recursive function to translate an effect list to a path sequence
optimize_effect | Run the optimizer to obtain symbolic bounds
optimize_effect_2 | Run the optimizer to obtain symbolic bounds
opt_effect | Compute a bound on the average causal effect
parse_constraints | Parse text that defines a the constraints
parse_effect | Parse text that defines a causal effect
plot.linearcausalproblem | Plot the graph from the causal problem with a legend describing attributes
plot_graphres | Plot the analyzed graph object
print.causalmodel | Print relevant information about the causal model
print.linearcausalproblem | Print the causal problem
querycheck | Check conditions on query
rdirichlet | Sample from a Dirichlet distribution
sample_distribution | Sample a distribution of observable probabilities that satisfy the causal model
simulate_bounds | Simulate bounds
specify_graph | Shiny interface to specify network structure and compute bounds
update_effect | Update the effect in a linearcausalproblem object