This package implements S4 classes and various tools for financial time series. Basic functions such as scaling and sorting, subsetting, mathematical operations and statistical functions are provided.

This package provides functions for Constraint Based Simulation using Flux Balance Analysis and informative analysis of the data generated during simulation.

This package implements methods that are useful in designing research studies and analyzing data, with particular emphasis on methods that are developed for or used within the behavioral, educational, and social sciences (broadly defined). That being said, many of the methods implemented within MBESS are applicable to a wide variety of disciplines. MBESS has a suite of functions for a variety of related topics, such as effect sizes, confidence intervals for effect sizes (including standardized effect sizes and noncentral effect sizes), sample size planning (from the accuracy in parameter estimation (AIPE), power analytic, equivalence, and minimum-risk point estimation perspectives), mediation analysis, various properties of distributions, and a variety of utility functions.

This package provides a Database Interface (DBI) compliant driver for R to access PostgreSQL database systems.

This package provides a simple git client for R based on libgit2 with support for SSH and HTTPS remotes. All functions in gert use basic R data types (such as vectors and data-frames) for their arguments and return values. User credentials are shared with command line git through the git-credential store and SSH keys stored on disk or ssh-agent.

This package provides implementations of a family of Lasso variants including Dantzig Selector, LAD Lasso, SQRT Lasso, Lq Lasso for estimating high dimensional sparse linear models.

This package provides tools for creating, viewing, and assessing qualitative palettes with many (20-30 or more) colors. See Coombes and colleagues (2019) https://doi:10.18637/jss.v090.c01.

This method identifies topological domains in genomes from Hi-C sequence data. The authors published an implementation of their method as an R script. This package originates from those original TopDom R scripts and provides help pages adopted from the original TopDom PDF documentation. It also provides a small number of bug fixes to the original code.

This is a package for ratios of count data such as obtained from RNA-seq are modelled using Bayesian statistics to derive posteriors for effects sizes. This approach is described in Erhard & Zimmer (2015) <doi:10.1093/nar/gkv696> and Erhard (2018) <doi:10.1093/bioinformatics/bty471>.

This package provides various methods for MRI tissue classification.

This package provides a high-level R interface to data files written using Unidata's netCDF library (version 4 or earlier), which are binary data files that are portable across platforms and include metadata information in addition to the data sets. Using this package, netCDF files can be opened and data sets read in easily. It is also easy to create new netCDF dimensions, variables, and files, in either version 3 or 4 format, and manipulate existing netCDF files.

This package provides a parallel backend for the %dopar% function using the multicore functionality of the parallel package.

This package provides a friendly interface for the construction of regular expressions. Regular expressions are a very powerful feature, however they are often difficult to interpret. Rex allows you to build complex regular expressions from human readable expressions

Machine Learning models are widely used and have various applications in classification or regression. Models created with boosting, bagging, stacking or similar techniques are often used due to their high performance, but such black-box models usually lack interpretability. The DALEX package contains various explainers that help to understand the link between input variables and model output.

This package runs R-code present in a pandoc markdown file and includes the resulting output in the resulting markdown file. This file can then be converted into any of the output formats supported by pandoc. The package can also be used as an engine for writing package vignettes.

Sending functions to remote processes can be wasteful of resources because they carry their environments with them. With this package, it is easy to create functions that are isolated from their environment. These isolated functions, also called crates, print to the console with their total size and can be easily tested locally before being sent to a remote.

latex2exp parses and converts LaTeX math formulas to R's plotmath expressions, used to enter mathematical formulas and symbols to be rendered as text, axis labels, etc. throughout R's plotting system.

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.

The package converts the input in any one of character, integer, numeric, factor, or an ordered type into POSIXct (or Date) objects, using one of a number of predefined formats, and relying on Boost facilities for date and time parsing.

Create interactive 3D scatter plots, network plots, and globes in R using the three.js visualization library.

This package provides flexible Bayesian estimation of IMIFA and related models, for nonparametrically clustering high-dimensional data. The IMIFA model conducts Bayesian nonparametric model-based clustering with factor analytic covariance structures without recourse to model selection criteria to choose the number of clusters or cluster-specific latent factors, mostly via efficient Gibbs updates. Model-specific diagnostic tools are also provided, as well as many options for plotting results, conducting posterior inference on parameters of interest, posterior predictive checking, and quantifying uncertainty.

ACDm is a package for Autoregressive Conditional Duration (ACD, Engle and Russell, 1998) models. It creates trade, price or volume durations from transactions (tic) data, performs diurnal adjustments, fits various ACD models and tests them.

This package provides simulation methods for the evolution of antibody repertoires. The heavy and light chain variable region of both human and C57BL/6 mice can be simulated in a time-dependent fashion. Both single lineages using one set of V-, D-, and J-genes or full repertoires can be simulated. The algorithm begins with an initial V-D-J recombination event, starting the first phylogenetic tree. Upon completion, the main loop of the algorithm begins, with each iteration representing one simulated time step. Various mutation events are possible at each time step, contributing to a diverse final repertoire.

This package provides convenience functions for advanced linear algebra with tensors and computation with datasets of tensors on a higher level abstraction. It includes Einstein and Riemann summing conventions, dragging, co- and contravariate indices, and parallel computations on sequences of tensors.