A tool for generating acronyms and initialisms from arbitrary text input.

Construct minimum-cost regular spanning subgraph as part of a
    non-parametric two-sample test for equality of distribution.

Provides a general toolkit for downloading, managing,
  analyzing, and presenting data from the U.S. Census
  (<https://www.census.gov/data/developers/data-sets.html>), including
  SF1 (Decennial short-form), SF3 (Decennial long-form), and the
  American Community Survey (ACS).  Confidence intervals provided with
  ACS data are converted to standard errors to be bundled with
  estimates in complex acs objects.  Package provides new methods to
  conduct standard operations on acs objects and present/plot data in
  statistically appropriate ways.

Main functionality is to provide the algorithmic complexity for
    short strings, an approximation of the Kolmogorov Complexity of a short
    string using the coding theorem method (see ?acss). The database containing
    the complexity is provided in the data only package acss.data, this package
    provides functions accessing the data such as prob_random returning the
    posterior probability that a given string was produced by a random process.
    In addition, two traditional (but problematic) measures of complexity are
    also provided: entropy and change complexity.

Data only package providing the algorithmic complexity of short strings, computed using the coding theorem method. For a given set of symbols in a string, all possible or a large number of random samples of Turing machines (TM) with a given number of states (e.g., 5) and number of symbols corresponding to the number of symbols in the strings were simulated until they reached a halting state or failed to end. This package contains data on 4.5 million strings from length 1 to 12 simulated on TMs with 2, 4, 5, 6, and 9 symbols. The complexity of the string corresponds to the distribution of the halting states of the TMs.

A book designed to meet the requirements of masters students. Tattar, P.N., Suresh, R., and Manjunath, B.G. "A Course in Statistics with R", J. Wiley, ISBN 978-1-119-15272-9.