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bayesAB 1.1.3

Minor Changes

  • Fix ggplot2 deprecation warning introduced in latest version.

bayesAB 1.1.2

Minor Changes

  • Fix documentation to reflect the changes to NormalInverseGamma in 1.1.0.

bayesAB 1.1.1

Minor Changes

  • Bug fixes for most recent version of ggplot2. Hopefully the API is stabe from here on out.
  • Fixed grab to correctly return the priors property in addition to posteriors and inputs.
  • Fixed the print generic for the bayesTestClosed types to error out informatively

bayesAB 1.1.0

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

bayesAB 1.0.0

Major Additions

  • Added grab and rename to retrieve and rename posteriors from your bayesTest object

    • Mostly useful in conjunction with combine in order to quickly chain together several bayesTests

  • Correctly hide legend for generic plots

  • Standardized prior parameters to have the same arguments as the plot{Dist} functions

    • This mostly changes prior inputs for bayesTest(distribution = c('normal', 'lognormal'))
    • This is a breaking change

Major Internal Changes

  • Moved distribution metadata from bayesTest$distribution to bayesTest$inputs$distribution to be consistent
  • Reconcile posterior names to always be A and B and not include the parameter name
  • A_data and B_data in inputs are now always lists by default to make combine work more simply
  • Big refactor of how bayesTest works internally. Dispatch per distribution is now only related to how the posterior is calculated.
  • Some error checking has been made more generic

Minor Tweaks/Fixed

  • Posterior Expected Loss now correctly displays 0 instead of NaN for that case
  • Numerous doc/examples/tests cleanup
  • Overall refactor of some methods, making it easier to read and contribute

bayesAB 0.7.0

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

bayesAB 0.6.0

Major Additions

  • First major CRAN release
  • 6 (+ 2) distributions
  • print, plot, summary generics
  • Easy plotting of distributions for quick visual inspection
  • combine tests as needed
  • 100% code coverage