The function \code{barcode()}
        produces a histogram-like plot of a distribution that shows
        granularity in the data.

Tools to generate unique identifier codes and
    printable barcoded labels for the management of biological samples.
    The creation of unique ID codes and printable PDF files can be
    initiated by standard commands, user prompts, or through a GUI addin
    for R Studio. Biologically informative codes can be included for
    hierarchically structured sampling designs.

To perform species identification using DNA barcodes.

Provides R data structures for Shakespeare's complete works, 
  as provided by Project Gutenberg <https:www.gutenberg.org/ebooks/100>.

Bayesian Additive Regression Kernels (BARK) provides
	an implementation for non-parametric function estimation using Levy
	Random Field priors for functions that may be represented as a
	sum of additive multivariate kernels.  Kernels are located at
	every data point as in Support Vector Machines, however, coefficients 
	may be heavily shrunk to zero under the Cauchy process prior, or even, 
	set to zero.  The number of active features is controlled by priors on
	precision parameters within the kernels, permitting feature selection. For 
	more details see Ouyang, Z (2008) "Bayesian Additive Regression Kernels",
	Duke University. PhD dissertation, Chapter 3 and Wolpert, R. L, Clyde, M.A, 
	and Tu, C. (2011) "Stochastic Expansions with Continuous Dictionaries Levy
	Adaptive Regression Kernels, Annals of Statistics Vol (39) pages 1916-1962 
	<doi:10.1214/11-AOS889>.

Barnard's unconditional test for 2x2 contingency tables.

Bayesian Additive Regression Trees (BART) provide flexible nonparametric modeling of covariates for continuous, binary, categorical and time-to-event outcomes.  For more information see Sparapani, Spanbauer and McCulloch <doi:10.18637/jss.v097.i01>.

Contains a variety of methods to generate typical causal inference estimates using Bayesian Additive Regression Trees (BART) as the underlying regression model (Hill (2012) <doi:10.1198/jcgs.2010.08162>).