Software

Cryptography

The Crypt::RC6 extension to Perl.

The Crypt::Serpent extension to Perl.

The batchmeans package for R (with Murali Haran).

This package provides consistent batch means estimation of Monte Carlo standard errors.

The CellularAutomaton package for R.

This package is an object-oriented implementation of one-dimensional cellular automata. It supports many of the features offered by Mathematica, including elementary rules, user-defined rules, radii, user-defined seeding, and plotting.

The copCAR package for R (with Emily Goren).

This package provides tools for applying the copCAR model (Hughes, 2015) to areal Bernoulli, negative binomial, or Poisson data.

The hash package for R.

This package implements a data structure similar to hashes in Perl and dictionaries in Python but with a purposefully R flavor. For objects of appreciable size, access using hashes outperforms native named lists and vectors. This package was authored by Christopher Brown. I am merely the package's maintainer.

This package provides tools for applying Krippendorff's Alpha methodology. Both the customary methodology and Hughes' methodology are supported, the former being preferred for larger datasets, the latter for smaller datasets. The framework supports common and user-defined distance functions, and can accommodate any number of units, any number of coders, and missingness. Interval estimation can be done in parallel for either methodology. The GitHub repository can be found here.

The lazygreedy package for R (with Bokgyeong Kang).

This package provides an R wrapper for a fast C++ implementation of the Lazy-Greedy spanning algorithm of Bouts, ten Brink, and Buchin (2014).

The mcmcse package for R (with James Flegal, Dootika Vats, Ning Dai, Kushagra Gupta, and Uttiya Maji).

This package provides tools for computing Monte Carlo standard errors (MCSE) in Markov chain Monte Carlo (MCMC) settings. MCSE computation for expectation and quantile estimators is supported. The package also provides functions for computing effective sample size and for plotting Monte Carlo estimates versus sample size.

The ngspatial package for R (with Xiaohui Cui).

This package provides tools for analyzing spatially aggregated data. The current version supports the sparse restricted spatial regression model of Hughes and Haran (2013), the centered autologistic model of Caragea and Kaiser (2009), and the Bayesian spatial filtering model of Hughes (2017).

The pearson7 package for R.

This package supports maximum likelihood inference for the Pearson VII distribution with shape parameter 3/2 and free location and scale parameters. This distribution is relevant when estimating the velocity of processive motor proteins.

The sklarsomega package for R.

This package provides tools for applying Sklar's Omega (Hughes, 2022) methodology to nominal scores, ordinal scores, percentages, counts, amounts, or balances. The framework can accommodate any number of units, any number of coders, and missingness; and can be used to measure agreement with a gold standard, intra-coder agreement, and/or inter-coder agreement.