Balancing Confounder Distributions with Forest Energy Balancing

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Documentation for package ‘forestBalance’ version 0.1.0

• DESCRIPTION file
• User guides, package vignettes and other documentation

Help Pages

forestBalance-package	forestBalance: Forest Kernel Energy Balancing for Causal Inference
compute_balance	Compute covariate balance diagnostics for a set of weights
forestBalance	forestBalance: Forest Kernel Energy Balancing for Causal Inference
forest_balance	Estimate ATE using forest-based kernel energy balancing
forest_kernel	Compute random forest proximity kernel from a GRF forest
get_leaf_node_matrix	Extract leaf node membership matrix from a GRF forest
kernel_balance	Kernel energy balancing weights via closed-form solution
leaf_node_kernel	Compute random forest proximity kernel from a leaf node matrix
leaf_node_kernel_Z	Build the sparse indicator matrix Z from a leaf node matrix
print.forest_balance	Print a forest_balance object
print.forest_balance_diag	Compute covariate balance diagnostics for a set of weights
print.summary.forest_balance	Summarize a forest_balance object
simulate_data	Simulate observational study data with confounding
summary.forest_balance	Summarize a forest_balance object