# 'LiNGAM' Algorithms for Causal Discovery

## Documentation for package ‘lingamr’ version 0.1.2

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

## Help Pages

as_bootstrap_result | Collapse an ImputationBootstrapResult into a BootstrapResult
autoplot.LiMResult | Plot the causal graph of a LiMResult with ggplot2
autoplot.LingamResult | Plot the causal graph of a LingamResult with ggplot2
autoplot.MultiGroupLingamResult | Plot one group of a MultiGroupLingamResult with ggplot2
autoplot.ParceLingamResult | Plot the causal graph of a ParceLingamResult with ggplot2
autoplot.RCDResult | Plot the causal graph of an RCDResult with ggplot2
bootstrap_with_imputation | Bootstrap with Multiple Imputation for Direct LiNGAM
check_var_stationarity | Check the stationarity of a fitted VAR-LiNGAM model
estimate_all_total_effects | Estimate the total causal effects between all variables at once
estimate_total_effect | Estimate the total causal effect between two specified variables
estimate_total_effect_parce | Estimate the total causal effect between two variables (ParceLiNGAM)
estimate_total_effect_rcd | Estimate the total causal effect between two variables (RCD)
estimate_var_total_effect | Estimate a total causal effect in a VAR-LiNGAM model
evaluate_model_fit | Evaluate model fit of an estimated causal graph
generate_lim_sample | Generate sample data for LiM (3 mixed variables)
generate_lingam_hard_sample | Generate a challenging sample data for Direct LiNGAM
generate_lingam_large_sample | Generate large-scale sample data to benchmark Direct LiNGAM scalability
generate_lingam_paradox_data | Generate Paradoxical Data Where DirectLiNGAM Struggles
generate_lingam_sample_10 | Generate 10-variable sample data for Direct LiNGAM
generate_lingam_sample_6 | Generate sample data for Direct LiNGAM (6 variables)
generate_multi_group_sample | Generate sample data for Multi-Group Direct LiNGAM (2 groups, 6 variables)
generate_parce_sample | Generate sample data with a latent confounder (for BottomUpParceLiNGAM)
generate_rcd_sample | Generate sample data with a latent confounder (for RCD)
generate_varlingam_sample | Generate sample data from a VAR-LiNGAM model
get_adjacency_matrix_summary | Create an adjacency matrix of representative causal-effect values from bootstrap results
get_causal_direction_counts | Get counts, proportions, and causal effects of causal directions
get_causal_order_stability | Evaluate the stability of the causal order from bootstrap
get_directed_acyclic_graph_counts | Get DAG counts
get_error_independence_p_values | Compute p-values for the independence test of the errors
get_error_independence_p_values_parce | Compute p-values for the independence of ParceLiNGAM residuals (HSIC-based)
get_error_independence_p_values_rcd | Compute p-values for the independence of RCD residuals (HSIC-based)
get_group_result | Extract a single group's result from a MultiGroupLingamResult
get_paths | Get all paths between two specified variables and their bootstrap probabilities
get_probabilities | Get bootstrap probabilities
get_total_causal_effects | Get a list of total causal effects
get_var_paths | Enumerate bootstrap paths between two variables in a VAR-LiNGAM model
get_var_probabilities | Bootstrap probabilities for a VAR-LiNGAM model
glance.LiMResult | Get a one-row summary of a LiMResult
glance.LingamResult | Get a one-row summary of a LingamResult
glance.MultiGroupLingamResult | Get a one-row summary of a MultiGroupLingamResult
glance.ParceLingamResult | Get a one-row summary of a ParceLingamResult
glance.RCDResult | Get a one-row summary of an RCDResult
lingam_direct | Direct LiNGAM
lingam_direct_bootstrap | Bootstrap for Direct LiNGAM
lingam_high_dim | High-Dimensional Direct LiNGAM
lingam_lim | LiM: LiNGAM for Mixed Data
lingam_multi_group | Multi-Group Direct LiNGAM
lingam_multi_group_bootstrap | Bootstrap for Multi-Group Direct LiNGAM
lingam_parce | Bottom-Up ParceLiNGAM
lingam_parce_bootstrap | Bootstrap for Bottom-Up ParceLiNGAM
lingam_rcd | RCD (Repetitive Causal Discovery)
lingam_rcd_bootstrap | Bootstrap for RCD
lingam_var | VAR-LiNGAM for time series causal discovery
lingam_var_bootstrap | Bootstrap for VAR-LiNGAM
make_prior_knowledge | Create a prior knowledge matrix
plot_adjacency | Plot a causal graph from an adjacency matrix with DiagrammeR
plot_bootstrap_probabilities | Draw bootstrap probabilities with DiagrammeR
plot_residual_qq | plot QQ
plot_varlingam_residual_qq | Q-Q plots of VAR-LiNGAM residuals
print.BootstrapResult | Display the contents of a BootstrapResult
print.causal_order_stability | print method for causal_order_stability
print.ImputationBootstrapResult | Print method for ImputationBootstrapResult
print.LiMResult | Print method for LiMResult
print.LingamResult | Print method for LingamResult
print.lingam_normality_test | Print method for lingam_normality_test
print.lingam_summary | print method for lingam_summary
print.MultiGroupBootstrapResult | Print method for MultiGroupBootstrapResult
print.MultiGroupLingamResult | Print method for MultiGroupLingamResult
print.ParceLingamResult | Print method for ParceLingamResult
print.RCDResult | Print method for RCDResult
print.VARBootstrapResult | Print a VARBootstrapResult
print.VARLiNGAMResult | Print method for VARLiNGAMResult
print.var_stationarity | Print method for var_stationarity
summary_lingam | Summarize the goodness-of-fit of a Direct LiNGAM model at once
test_residual_normality | Test normality of residuals from Direct LiNGAM
test_varlingam_residual_normality | Test the non-Gaussianity of VAR-LiNGAM residuals
test_varlingam_residual_normality_all | Run several normality tests on VAR-LiNGAM residuals at once
tidy.BootstrapResult | Convert a BootstrapResult to a tidy data.frame
tidy.ImputationBootstrapResult | Convert an ImputationBootstrapResult to a tidy data.frame
tidy.LiMResult | Convert a LiMResult to a tidy data.frame
tidy.LingamResult | Convert a LingamResult to a tidy data.frame
tidy.MultiGroupBootstrapResult | Convert a MultiGroupBootstrapResult to a tidy data.frame
tidy.MultiGroupLingamResult | Convert a MultiGroupLingamResult to a tidy data.frame
tidy.ParceLingamResult | Convert a ParceLingamResult to a tidy data.frame
tidy.RCDResult | Convert an RCDResult to a tidy data.frame