Changes and New Features in 1.6 (2018-03-19):

	* for binary outcomes, new default for ntree=50
	  (change inadvertently omitted from v1.4 below)

        * enhancement: recur.pre.bart, recur.bart and mc.recur.bart
	  can now handle NA entries in the times and delta matrices

	* enhancement: for time-to-event outcomes, new optional 
	  K parameter which coarsens time per the quantiles
          1/K, 2/K, ..., K/K.

	* fix bug: x.test/x.test2 now properly transposed if needed
	  for post-processing

	* fix bug: sparse Dirichlet prior now corrected for 
	  random theta update.  Thanks to Antonio Linero for
	  the detailed bug report.

Changes and New Features in 1.5 (2018-02-08):

        * fix bug: ambiguous call of floor surrounding integer division

	* fix bug: x.test is not an argument of recur.pre.bart

Changes and New Features in 1.4 (2018-02-02):

	* for binary outcomes, new default for ntree=50

        * fixed library bloat on Linux with strip

	* x.train and x.test can be supplied as data.frames
	  which contain factors as stated in the documentation

	* cutpoints now based on data itself, i.e., binary or
	  ordinal covariates.  Similarly, you can request 
	  quantiles via the usequants setting. 

	* sparse variable selection now available with the
	  sparse=TRUE argument; see the documentation

	* new vignettes

	* new function, mc.lbart, for Logistic BART in parallel

	* mbart updated to equivalent functionality as other functions

	* new function, mc.mbart, for Multinomial BART in parallel

Changes and New Features in 1.3 (2017-09-18):

        * new examples in demo directory

	* return ndpost values rather ndpost/keepevery

	* for calling BART directly from C++, you can
	  now use the RNG provided by Rmath or the STL random class
	  see the improved example in cxx-ex

	* new predict S3 methods, see predict.wbart and other
	  predict variants

	* Added Geweke diagnostics for pbart, surv.bart, etc.
	  See gewekediag which is adapted from the coda package

	* Logistic BART added for binary outcomes; see lbart

	* Multinomial BART added for categorical outcomes; see mbart

Changes and New Features in 1.2 (2017-04-30):

	* you can now call BART directly from C++ with the Rmath library 
	  see new header rn.h and the example in cxx-ex

Changes and New Features in 1.1 (2017-04-13):

	* No user visible changes: bug-fix release

Changes and New Features in 1.0 (2017-04-07):

	* First release on CRAN
