Provides pipe-style interface for 'data.table'. Package preserves all 'data.table' features without
              significant impact on performance. 'let' and 'take' functions are simplified interfaces for most common data
              manipulation tasks. For example, you can write 'take(mtcars, mean(mpg), by = am)' for aggregation or 
              'let(mtcars, hp_wt = hp/wt, hp_wt_mpg = hp_wt/mpg)' for modification. Use 'take_if/let_if' for conditional
              aggregation/modification. Additionally there are some conveniences such as automatic 'data.frame' 
              conversion to 'data.table'.

An object that supports automatic differentiation
    of matrix- and multidimensional-valued functions with 
    respect to multidimensional independent variables. 
    Automatic differentiation is via 'forward accumulation'.

Tools for the analysis of population differences
    using the Major Histocompatibility Complex (MHC) genotypes of samples
    having a variable number of alleles (1-4) recorded for each
    individual.  A hierarchical Dirichlet-Multinomial model on the
    genotype counts is used to pool small samples from multiple
    populations for pairwise tests of equality.  Bayesian inference is
    implemented via the 'rstan' package.  Bootstrapped and posterior
    p-values are provided for chi-squared and likelihood ratio tests of
    equal genotype probabilities.

Estimates average treatment effects using model average double robust (MA-DR) estimation. The MA-DR estimator is defined as weighted average of double robust estimators, where each double robust estimator corresponds to a specific choice of the outcome model and the propensity score model. The MA-DR estimator extend the desirable double robustness property by achieving consistency under the much weaker assumption that either the true propensity score model or the true outcome model be within a specified, possibly large, class of models.

Provides a framework which should improve reproducibility and
    transparency in data processing. It provides functionality such as
    automatic meta data creation and management, rudimentary quality
    management, data caching, work-flow management and data aggregation.
    * The title is a wish not a promise. By no means we expect this
    package to deliver everything what is needed to achieve full
    reproducibility and transparency, but we believe that it supports
    efforts in this direction.