.check_A                Check Number of Observations for Inference
.check_first_batch      Check First Batch Validity
.check_shape            Check Shape Compatibility of Probability
                        Objects
LinTSModel              Linear Thompson Sampling model.
aw_estimate             Estimate policy value via non-contextual
                        adaptive weighting.
aw_scores               Compute AIPW/doubly robust scores.
aw_var                  Variance of policy value estimator via
                        non-contextual adaptive weighting.
calculate_balwts        Calculate balancing weight scores.
calculate_continuous_X_statistics
                        Estimate/variance of policy evaluation via
                        contextual weighting.
draw_thompson           Thompson Sampling draws.
estimate                Estimate/variance of policy evaluation via
                        non-contextual weighting.
generate_bandit_data    Generate classification data.
ifelse_clip             Clip lamb values between a minimum x and
                        maximum y.
impose_floor            Impose probability floor.
output_estimates        Policy evaluation with adaptively generated
                        data.
plot_cumulative_assignment
                        Plot cumulative assignment for bandit
                        experiment.
ridge_init              Ridge Regression Initialization for Arm
                        Expected Rewards
ridge_muhat_lfo_pai     Leave-future-out ridge-based estimates for arm
                        expected rewards.
ridge_update            Updates ridge regression matrices.
run_experiment          Run an experiment using Thompson Sampling.
simple_tree_data        Generate simple tree data.
stick_breaking          Stick breaking function.
twopoint_stable_var_ratio
                        Calculate allocation ratio for a two-point
                        stable-variance bandit.
update_thompson         Update linear Thompson Sampling model.
