BayesAB Versions Save

🐢 bayesAB: Fast Bayesian Methods for A/B Testing

v1.1.3

2 years ago

Minor release fixing deprecation issues caused by new ggplot version.

v1.1.2

4 years ago

Minor release for fixing a bug caused by latest release of ggplot2. No API changes.

v1.1.0

6 years ago

Breaking

  • Changed conjugate prior of Normal/LogNormal distributions to be the NormalInverseGamma distribution from a combination of the Normal and Inverse Gamma distributions. This distribution is bivariate and gives us a 2d estimate for both x and sig_sq. The params for this distribution are mu, lambda, alpha, beta and are different from the old priors that Normal/LogNormal were expecting.
    • Various doc changes to illustrate these changes and new expectations

Major Changes

  • Fix closed form distributions and added tests
  • Calculation Posterior Expected Loss is now correct and represents a true loss function
  • Added plotNormalInvGamma

Minor Changes

  • Colors for sample plots are now hardcoded (red for > 0 and blue for < 0)
  • Plots are truncated at the extremes to avoid very long tails

v1.0.0

6 years ago

0.6.0

7 years ago

First CRAN release.

v0.7.0

7 years ago

Major Additions

  • added banditize and deployBandit to turn your bayesTest object into a Bayesian multi-armed bandit and deploy as a JSON API respectively.
  • Added programmatic capabilities on top of existing interactive uses for plot generic function
    • You can now assign plot(bayesTestObj) to a variable and not have it automatically plot.
  • Added quantile summary of calculated posteriors to the output of summary.bayesTest
  • Added Posterior Expected Loss to output of summary.bayesTest
    • This is useful to know when to stop your Bayesian AB Test
    • Supports the risk of choosing 'B' over 'A' (ordering is important) and makes more sense if A > B currently in the test

Minor Tweaks/Fixes

  • outputs from plot generics are now explicitly ggplot objects and can be modified as such
    • You can input your own titles/axis labels/etc if the defaults don't fit your use case