NEWS.md
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.
Added grab and rename to retrieve and rename posteriors from your bayesTest object
combine in order to quickly chain together several bayesTestsCorrectly hide legend for generic plots
Standardized prior parameters to have the same arguments as the plot{Dist} functions
bayesTest(distribution = c('normal', 'lognormal'))
distribution metadata from bayesTest$distribution to bayesTest$inputs$distribution to be consistentA and B and not include the parameter nameA_data and B_data in inputs are now always lists by default to make combine work more simplybayesTest works internally. Dispatch per distribution is now only related to how the posterior is calculated.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
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