Probability Distributions as S3 Objects (distributions3)
Tools to create and manipulate probability
distributions using S3. Generics random(), pdf(), cdf() and
quantile() provide replacements for base R’s r/d/p/q style functions.
Functions and arguments have been named carefully to minimize
confusion for students in intro stats courses. The documentation for
each distribution contains detailed mathematical notes.

Threshold Matching for Thick Description for Optimal Matching in
Observational Studies
Conducts several closest matched pairs to strengthen a matched quantitative comparison of many pairs by thick description in observational studies.
Rosenbaum, P. R. (2017). <doi:10.1080/10618600.2016.1152971>.

A friendly MCMC framework (fmcmc)
Provides a friendly (flexible) Markov Chain Monte Carlo (MCMC) framework for implementing Metropolis-Hastings algorithm in a modular way allowing users to specify automatic convergence checker, personalized transition kernels, and out-of-the-box multiple MCMC chains using parallel computing. Most of the methods implemented in this package can be found in Brooks et al. (2011, ISBN 9781420079425).

Testing One Hypothesis Multiple Times (TOHM)
Approximations of global p-values when testing hypothesis in presence of non-identifiable nuisance parameters. The method relies on the Euler characteristic heuristic and the expected Euler characteristic is efficiently computed by in Algeri and van Dyk (2018) <arXiv:1803.03858>.

Nonparametric Regression (npreg)
Multiple and generalized nonparametric regression using smoothing spline ANOVA models and generalized additive models. Includes support for Gaussian and non-Gaussian responses, smoothers for multiple types of predictors, interactions between smoothers of mixed types, and eight different methods for smoothing parameter selection.