Bayesian Inference for A|B and Bandit Marketing Tests

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Documentation for package ‘grizbayr’ version 1.3.5

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

Help Pages

calculate_multi_rev_per_session	Calculate Multi Rev Per Session
calculate_total_cm	Calculate Total CM
estimate_all_values	Estimate All Values
estimate_lift	Estimate Lift Distribution
estimate_lift_vs_baseline	Estimate Lift vs Baseline
estimate_loss	Estimate Loss
estimate_value_remaining	Estimate Value Remaining
estimate_win_prob	Estimate Win Probability
estimate_win_prob_given_posterior	Estimate Win Probability Given Posterior Distribution
estimate_win_prob_vs_baseline	Estimate Win Probability vs. Baseline
estimate_win_prob_vs_baseline_given_posterior	Estimate Win Probability vs. Baseline Given Posterior
find_best_option	Find Best Option
impute_missing_options	Impute Missing Options
is_prior_valid	Is Prior Valid
is_winner_max	Is Winner Max
rdirichlet	Random Dirichlet
sample_cm_per_click	Sample CM Per Click
sample_conv_rate	Sample Conversion Rate
sample_cpa	Sample Cost Per Activation (CPA)
sample_cpc	Sample Cost Per Click
sample_ctr	Sample Click Through Rate
sample_from_posterior	Sample From Posterior
sample_multi_rev_per_session	Sample Multiple Revenue Per Session
sample_page_views_per_session	Sample Page Views Per Session (Visit)
sample_response_rate	Sample Response Rate
sample_rev_per_session	Sample Rev Per Session
sample_session_duration	Sample Session Duration
sample_total_cm	Sample Total CM (Given Impression Count)
update_beta	Update Beta
update_dirichlet	Update Dirichlet Distribution
update_gamma	Update Gamma
validate_data_values	Validate Data Values
validate_input_column	Validate Input Column
validate_input_df	Validate Input DataFrame
validate_posterior_samples	Validate Posterior Samples Dataframe
validate_priors	Validate Priors
validate_wrt_option	Validate With Respect To Option