The Lawson-Hanson Algorithm for Non-Negative Least Squares (NNLS)

An R interface to the Lawson-Hanson implementation of an algorithm for non-negative least squares (NNLS). Also allows the combination of non-negative and non-positive constraints.

Interface with Google Cloud Storage API

Interact with Google Cloud Storage < https://cloud.google.com/storage/> API in R. Part of the 'cloudyr' < https://cloudyr.github.io/> project.

Miscellaneous, Analytic R Kernels

Miscellaneous functions and wrappers for development in other packages created, maintained by Jordan Mark Barbone.

Web Application Framework for R

Makes it incredibly easy to build interactive web applications with R. Automatic "reactive" binding between inputs and outputs and extensive prebuilt widgets make it possible to build beautiful, responsive, and powerful applications with minimal effort.

Record Linkage Toolkit

Functions to assist in performing probabilistic record linkage and deduplication: generating pairs, comparing records, em-algorithm for estimating m- and u-probabilities (I. Fellegi & A. Sunter (1969) , T.N. Herzog, F.J. Scheuren, & W.E. Winkler (2007), "Data Quality and Record Linkage Techniques", ISBN:978-0-387-69502-0), forcing one-to-one matching. Can also be used for pre- and post-processing for machine learning methods for record linkage. Focus is on memory, CPU performance and flexibility.

Compositional Data Analysis

Provides functions for the consistent analysis of compositional data (e.g. portions of substances) and positive numbers (e.g. concentrations) in the way proposed by J. Aitchison and V. Pawlowsky-Glahn.

Phylogenetic Linear Regression

Provides functions for fitting phylogenetic linear models and phylogenetic generalized linear models. The computation uses an algorithm that is linear in the number of tips in the tree. The package also provides functions for simulating continuous or binary traits along the tree. Other tools include functions to test the adequacy of a population tree.

R Interface to Stan

User-facing R functions are provided to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the 'StanHeaders' package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via 'variational' approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.

Toolbox for Pseudo and Quasi Random Number Generation and Random Generator Tests

Provides (1) pseudo random generators - general linear congruential generators, multiple recursive generators and generalized feedback shift register (SF-Mersenne Twister algorithm () and WELL () generators); (2) quasi random generators - the Torus algorithm, the Sobol sequence, the Halton sequence (including the Van der Corput sequence) and (3) some generator tests - the gap test, the serial test, the poker test, see, e.g., Gentle (2003) . Take a look at the Distribution task view of types and tests of random number generators. The package can be provided without the 'rngWELL' dependency on demand. Package in Memoriam of Diethelm and Barbara Wuertz.

Graphical Analysis of Structural Causal Models

A port of the web-based software 'DAGitty', available at < https://dagitty.net>, for analyzing structural causal models (also known as directed acyclic graphs or DAGs). This package computes covariate adjustment sets for estimating causal effects, enumerates instrumental variables, derives testable implications (d-separation and vanishing tetrads), generates equivalent models, and includes a simple facility for data simulation.