# bayesAB 1.1.1 Unreleased

## 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 2017-09-26

## 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 2017-07-23

## 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 2016-10-09

## 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 2016-09-13

## 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