Bayesian geostatistical modeling of Gaussian processes using a
    reparameterized and marginalized posterior sampling (RAMPS) algorithm
    designed to lower autocorrelation in MCMC samples.  Package performance is
    tuned for large spatial datasets.

R-based access to mass-spectrometry (MS) data. While many packages 
  exist to process MS data, many of these make it difficult to 
  access the underlying mass-to-charge ratio (m/z), intensity, and 
  retention time of the files 
  themselves. This package is designed to format MS data in a tidy fashion and 
  allows the user perform the plotting and analysis.

Provides a solution path for Reinforced Angle-based Multicategory 
    Support Vector Machines, with linear learning, polynomial learning, and 
    Gaussian kernel learning. C. Zhang, Y. Liu, J. Wang and H. Zhu. (2016) 
    <doi:10.1080/10618600.2015.1043010>.

Provides randomization tests and graphical diagnostics for assessing randomized assignment and covariate balance for a binary treatment variable. See Branson (2021) <arXiv:1804.08760> for details.

Implements the algorithm by Pourahmadi and Wang (2015) <doi:10.1016/j.spl.2015.06.015> for generating a random p x p correlation matrix. Briefly, the idea is to represent the correlation matrix using Cholesky factorization and p(p-1)/2 hyperspherical coordinates (i.e., angles), sample the angles from a particular distribution and then convert to the standard correlation matrix form. The angles are sampled from a distribution with pdf proportional to sin^k(theta) (0 < theta < pi, k >= 1) using the efficient sampling algorithm described in Enes Makalic and Daniel F. Schmidt (2018) <arXiv:1809.05212>.

Generate random positions (latitude/longitude), 
    Well-known text ('WKT') points or polygons, or 'GeoJSON' points or 
    polygons.

A novel numerical algorithm that provides functionality for estimating the exact 95% confidence interval of the location parameter in the random effects model, and is much faster than the naive method. Works best when the number of studies is between 6-20.