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 bayesTest
sCorrectly 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