BayesPostEst 0.3.2
- Updated dependencies per CRAN warnings (#82)
- Added 7 packages used for testing from suggests to imports
BayesPostEst 0.3.1
- Removed package dependency on JAGS. Since rjags and R2jags were in
the package Imports previously, and they in turn depend on a JAGS
installed, the package would not install without JAGS. Now, all specific
MCMC implementations are in the package Suggests and the package can be
installed in an agnostic way without the need for JAGS, Stan, or any
other specific MCMC library.
- Conditional was added in the vignette for these packages (#77)
- There were several changes in mcmcRocPrc:
- The function has now become a generic with S3 methods for different
types of input, e.g. “rjags” objects created by [R2jags::jags()] or
“stanfit” via [rstan::stan()]. The default method takes a matrix of
predicted probabilities and vector of observed outcomes as input, thus
allowing any posterior sampling method to be accommodated. (#5)
- Added print, plot, as.data.frame methods for “mcmcRocPrc” objects
created with mcmcRocPrc(). (#32)
- Fixed several errors in documentation code examples. (#64)
- Added README.rmd to render images.
- Updated plots to a minimalist theme in documentation
- Updated master branch name to main
- Moved from Travis to GH-Actions
BayesPostEst 0.3.0
- Planned: Created website through pkgdown
- Added:
plot
method for mcmcFD
objects and
warn that mcmcFDplot
is deprecated
BayesPostEst 0.2.1
- Added ‘stringsAsFactors = TRUE’ for new data.frame() default with R
4.0.0
BayesPostEst 0.2.0
- Added functions
mcmcCoefPlot()
and
mcmcMargEff()
.
- Added corresponding website and static docs using pkgdown.
- Added function
mcmcRocPrcGen()
. This function takes
generalized objects and has the same functionality as
mcmcRocPrc()
, which only works for jags objects currently.
It should be noted that mcmcRocPrcGen()
works much more
slowly than mcmcRocPrc()
. Future version aim to merge and
improve upon these functions.
BayesPostEst 0.1.0
- Added a
NEWS.md
file to track changes to the
package.
- Improved
mcmcRocPrc()
speed by replacing imported ROCR
functions with faster custom ROC and PR curve calculators. The test
example with “fullsims = TRUE” should now take 2s or less to run instead
of the previous 10-30s. (#25)
- Removed ROCR package from dependencies.
- Changed the
mcmcRocPrc()
interface. Instead of
pre-calculating several data matrices, the function now takes a fitted
“rjags” object ([R2jags::jags()]) as input along with names of the
dependent and independent variables that were used in the model.
BayesPostEst 0.0.1