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  "Title": "Bayesian Inference for A|B and Bandit Marketing Tests",
  "Version": "1.3.5",
  "Author": "Ryan Angi",
  "Maintainer": "Ryan Angi <angi.ryan@gmail.com>",
  "Description": "Uses simple Bayesian conjugate prior update rules to\ncalculate the win probability of each option, value remaining\nin the test, and percent lift over the baseline for various\nmarketing objectives. References: Fink, Daniel (1997) \"A\nCompendium of Conjugate Priors\"\n<https://www.johndcook.com/CompendiumOfConjugatePriors.pdf>.\nStucchio, Chris (2015) \"Bayesian A/B Testing at VWO\"\n<https://vwo.com/downloads/VWO_SmartStats_technical_whitepaper.pdf>.",
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  "Repository": "https://r-angi.r-universe.dev",
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    "update_gamma",
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      "page": "calculate_multi_rev_per_session",
      "title": "Calculate Multi Rev Per Session",
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        "calculate_multi_rev_per_session"
      ]
    },
    {
      "page": "calculate_total_cm",
      "title": "Calculate Total CM",
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      ]
    },
    {
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      "title": "Estimate All Values",
      "topics": [
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      ]
    },
    {
      "page": "estimate_lift",
      "title": "Estimate Lift Distribution",
      "topics": [
        "estimate_lift"
      ]
    },
    {
      "page": "estimate_lift_vs_baseline",
      "title": "Estimate Lift vs Baseline",
      "topics": [
        "estimate_lift_vs_baseline"
      ]
    },
    {
      "page": "estimate_loss",
      "title": "Estimate Loss",
      "topics": [
        "estimate_loss"
      ]
    },
    {
      "page": "estimate_value_remaining",
      "title": "Estimate Value Remaining",
      "topics": [
        "estimate_value_remaining"
      ]
    },
    {
      "page": "estimate_win_prob",
      "title": "Estimate Win Probability",
      "topics": [
        "estimate_win_prob"
      ]
    },
    {
      "page": "estimate_win_prob_given_posterior",
      "title": "Estimate Win Probability Given Posterior Distribution",
      "topics": [
        "estimate_win_prob_given_posterior"
      ]
    },
    {
      "page": "estimate_win_prob_vs_baseline",
      "title": "Estimate Win Probability vs. Baseline",
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      ]
    },
    {
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      "title": "Estimate Win Probability vs. Baseline Given Posterior",
      "topics": [
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      ]
    },
    {
      "page": "find_best_option",
      "title": "Find Best Option",
      "topics": [
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      ]
    },
    {
      "page": "impute_missing_options",
      "title": "Impute Missing Options",
      "topics": [
        "impute_missing_options"
      ]
    },
    {
      "page": "is_prior_valid",
      "title": "Is Prior Valid",
      "topics": [
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      ]
    },
    {
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      "title": "Is Winner Max",
      "topics": [
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      "page": "rdirichlet",
      "title": "Random Dirichlet",
      "topics": [
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      ]
    },
    {
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      "title": "Sample CM Per Click",
      "topics": [
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      ]
    },
    {
      "page": "sample_conv_rate",
      "title": "Sample Conversion Rate",
      "topics": [
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      ]
    },
    {
      "page": "sample_cpa",
      "title": "Sample Cost Per Activation (CPA)",
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      ]
    },
    {
      "page": "sample_cpc",
      "title": "Sample Cost Per Click",
      "topics": [
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    },
    {
      "page": "sample_ctr",
      "title": "Sample Click Through Rate",
      "topics": [
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    },
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      "title": "Sample From Posterior",
      "topics": [
        "sample_from_posterior"
      ]
    },
    {
      "page": "sample_multi_rev_per_session",
      "title": "Sample Multiple Revenue Per Session",
      "topics": [
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      "page": "sample_page_views_per_session",
      "title": "Sample Page Views Per Session (Visit)",
      "topics": [
        "sample_page_views_per_session"
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    },
    {
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      "title": "Sample Response Rate",
      "topics": [
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      "title": "Sample Rev Per Session",
      "topics": [
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    },
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      "title": "Sample Session Duration",
      "topics": [
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      "title": "Sample Total CM (Given Impression Count)",
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