'LiNGAM' Algorithms for Causal Discovery


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Documentation for package ‘lingamr’ version 0.1.2

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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