This package provides utilities for working with Google APIs. This includes functions and classes for handling common credential types and for preparing, executing, and processing HTTP requests.

This package provides assorted routines for combinatorics.

This package runs tests using the testthat package but allows for multiple attempts for a single test. This is useful for noisy or flaky tests that generally pass but can fail due to occasional random errors, such as numeric instability or using random data.

Tree based algorithms can be improved by introducing boosting frameworks. LightGBM is one such framework, based on Ke, Guolin et al. (2017). This package offers an R interface to work with it. It is designed to be distributed and efficient with the following goals:

1. Faster training speed and higher efficiency;

2. lower memory usage;

3. better accuracy;

4. parallel learning supported; and

5. capable of handling large-scale data.

This is a collection of econometric functions for performance and risk analysis. This package aims to aid practitioners and researchers in utilizing the latest research in analysis of non-normal return streams. In general, it is most tested on return (rather than price) data on a regular scale, but most functions will work with irregular return data as well, and increasing numbers of functions will work with P&L or price data where possible.

This package implements numerically-stable Gauss-Hermite quadrature rules and utility functions for adaptive GH quadrature.

This package exposes R bindings to jsTree, a JavaScript library that supports interactive trees, to enable rich, editable trees in Shiny.

This R package downloads labeled single-cell RNA-seq data from PanglaoDB. It merges the data into a Seurat object for streamlined analysis.

This package provides an exact Goodness-of-Fit test for multinomial data with fixed probabilities. It can be used to determine whether a set of counts fits a given expected ratio. To see whether a set of observed counts fits an expectation, one can examine all possible outcomes with xmulti() or a random sample of them with xmonte() and find the probability of an observation deviating from the expectation by at least as much as the observed. As a measure of deviation from the expected, one can use the log-likelihood ratio, the multinomial probability, or the classic chi-square statistic. A histogram of the test statistic can also be plotted and compared with the asymptotic curve.

This package displays a progress bar in the R console for long running computations taking place in C++ code, and support for interrupting those computations even in multithreaded code, typically using OpenMP.

Building on the infrastructure provided by the lattice package, this package provides several new high-level graphics functions and methods, as well as additional utilities such as panel and axis annotation functions.

This package provides routines to find the root of nonlinear functions, and to perform steady-state and equilibrium analysis of ordinary differential equations (ODE). It includes routines that:

1. generate gradient and jacobian matrices (full and banded),

2. find roots of non-linear equations by the Newton-Raphson method,

3. estimate steady-state conditions of a system of (differential) equations in full, banded or sparse form, using the Newton-Raphson method, or by dynamically running,

4. solve the steady-state conditions for uni- and multicomponent 1-D, 2-D, and 3-D partial differential equations, that have been converted to ordinary differential equations by numerical differencing (using the method-of-lines approach).

This package provides a platform-independent API to access the operating system's credential store. It currently supports Keychain on macOS, Credential Store on Windows, the Secret Service API on GNU/Linux, and a simple, platform independent store implemented with environment variables. Additional storage back-ends can be added easily.

Single cell RNA sequencing datasets can be large, consisting of matrices that contain expression data for several thousand features across several thousand cells. This package is designed to easily install, manage, and learn about various single-cell datasets, provided Seurat objects and distributed as independent packages.

This package provides functions for drawing and calibrating samples.

This package lets you use syntax inspired by the package glue to extract matched substrings in a more intuitive and compact way than by using standard regular expressions.

This package performs penalized multivariate analysis: a penalized matrix decomposition, sparse principal components analysis, and sparse canonical correlation analysis.

This package provides a compilation of extra ggplot2 themes, scales and utilities, including a spell check function for plot label fields and an overall emphasis on typography.

This package provides several cluster-robust variance estimators (i.e., sandwich estimators) for ordinary and weighted least squares linear regression models, including the bias-reduced linearization estimator introduced by Bell and McCaffrey (2002) http://www.statcan.gc.ca/pub/12-001-x/2002002/article/9058-eng.pdf and developed further by Pustejovsky and Tipton (2017) doi:10.1080/07350015.2016.1247004. The package includes functions for estimating the variance- covariance matrix and for testing single- and multiple-contrast hypotheses based on Wald test statistics. Tests of single regression coefficients use Satterthwaite or saddle-point corrections. Tests of multiple-contrast hypotheses use an approximation to Hotelling's T-squared distribution. Methods are provided for a variety of fitted models, including lm() and mlm objects, glm(), ivreg (from package AER), plm() (from package plm), gls() and lme() (from nlme), robu() (from robumeta), and rma.uni() and rma.mv() (from metafor).

This package provides a parallel estimation of the mutual information based on entropy estimates from k-nearest neighbors distances and algorithms for the reconstruction of gene regulatory networks.

This package provides an easy way to determine which directories on the user's computer should be used to save data, caches and logs. It is a port of Python's Appdirs to R.

This package provides a simple and flexible way to generate Circos 2D track plot images. The types of plots include: heatmap, histogram, lines, scatterplot, tiles and plot items for further decorations include connector, link (lines and ribbons), and text (gene) label. All functions require only R graphics packages that comes with the base installation.

This package allows clinicians to predict the rate and severity of future acute exacerbation in Chronic Obstructive Pulmonary Disease (COPD) patients, based on the clinical prediction model published in Adibi et al. (2019) doi:10.1101/651901.

This package implements a simple key-value style database where character string keys are associated with data values that are stored on the disk. A simple interface is provided for inserting, retrieving, and deleting data from the database. Utilities are provided that allow filehash databases to be treated much like environments and lists are already used in R. These utilities are provided to encourage interactive and exploratory analysis on large datasets.