partitionMetric computes a distance between two partitions
        of a set.

Additive partitions of integers.  Enumerates the
  partitions, unequal partitions, and restricted partitions of an
  integer; the three corresponding partition functions are also given.
  Set partitions and now compositions and riffle shuffles are
  included.

Miscellaneous utilities for parallelizing large
   computations.  Alternative to MapReduce.
   File splitting and distributed operations such as sort and aggregate.
   "Software Alchemy" method for parallelizing most statistical methods,
   presented in N. Matloff, Parallel Computation for Data Science,
   Chapman and Hall, 2015.  Includes a debugging aid.

Partitioning the R2 of GLMMs into variation explained by each 
    predictor and combination of predictors using semi-partial (part) R2 and
    inclusive R2. Methods are based on the R2 for GLMMs described in
    Nakagawa & Schielzeth (2013) and Nakagawa, Johnson & Schielzeth (2017).

Basic functions to fit and predict periodic autoregressive time series models. These models are discussed in the book P.H. Franses (1996) "Periodicity and Stochastic Trends in Economic Time Series", Oxford University Press. Data set analyzed in that book is also provided. NOTE: the package was orphaned during several years. It is now only maintained, but no major enhancements are expected, and the maintainer cannot provide any support.

Datetimes and timestamps are invariably an imprecise notation, with any
    partial representation implying some amount of uncertainty. To handle this,
    'parttime' provides classes for embedding partial missingness as a central
    part of its datetime classes. This central feature allows for more ergonomic
    use of datetimes for challenging datetime computation, including
    calculations of overlapping date ranges, imputations, and more thoughtful
    handling of ambiguity that arises from uncertain time zones. This package was
    developed first and foremost with pharmaceutical applications in mind, but
    aims to be agnostic to application to accommodate general use cases just as
    conveniently.