This package provides model-robust standard error estimators for cross-sectional, time series, clustered, panel, and longitudinal data.

This package provides simple utility functions to read from and write to the system clipboards.

With this package you can add in-app user authentication to Shiny, allowing you to secure publicly hosted apps and build dynamic user interfaces from user information.

This package provides classes and methods to locate, setup, subset, navigate and iterate file sets, i.e. sets of files located in one or more directories on the file system. The API is designed such that these classes can be extended via inheritance to provide a richer API for special file formats. Moreover, a specific name format is defined such that filenames and directories can be considered to have full names which consists of a name followed by comma-separated tags. This adds additional flexibility to identify file sets and individual files.

This package enables the use of emoji and the Font Awesome glyphs in both base and ggplot2 graphics.

This package provides flexible parametric models for time-to-event data, including the Royston-Parmar spline model, generalized gamma and generalized F distributions. Any user-defined parametric distribution can be fitted, given at least an R function defining the probability density or hazard. There are also tools for fitting and predicting from fully parametric multi-state models.

This tool takes longitudinal dataset as input and analyzes if there is significant change of the features over time (a proxy for treatments), while detects and controls for covariates simultaneously. LongDat is able to take in several data types as input, including count, proportion, binary, ordinal and continuous data. The output table contains p values, effect sizes and covariates of each feature, making the downstream analysis easy.

This package contains various routines for drawing ellipses and ellipse-like confidence regions, implementing the plots described in Murdoch and Chow (1996), A graphical display of large correlation matrices, The American Statistician 50, 178-180. There are also routines implementing the profile plots described in Bates and Watts (1988), Nonlinear Regression Analysis and its Applications.

Stringr is a consistent, simple and easy to use set of wrappers around the fantastic stringi package. All function and argument names (and positions) are consistent, all functions deal with "NA"'s and zero length vectors in the same way, and the output from one function is easy to feed into the input of another.

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 package arranges data by a set of methods. It uses rearrangers to reorder data points and mutators to change their values. From basic utilities, to centering the greatest value, to swirling in 3-dimensional space, rearrr enables creativity when plotting and experimenting with data.

This package provides tools to fit and predict with the high-dimensional principal fitted components model. This model is described by Cook, Forzani, and Rothman (2012) doi:10.1214/11-AOS962.

This package provides a collection of tests, data sets, and examples for diagnostic checking in linear regression models. Furthermore, some generic tools for inference in parametric models are provided.

This package provides airline on-time data for all flights departing NYC in 2013. It also includes useful metadata on airlines, airports, weather, and planes.

This package provides bindings to libsodium: a library for encryption, decryption, signatures, password hashing and more. Sodium uses curve25519, a Diffie-Hellman function by Daniel Bernstein, which has become very popular after it was discovered that the NSA had backdoored Dual EC DRBG.

dplyr is the next iteration of plyr. It is focused on tools for working with data frames. It has three main goals: 1) identify the most important data manipulation tools needed for data analysis and make them easy to use in R; 2) provide fast performance for in-memory data by writing key pieces of code in C++; 3) use the same code interface to work with data no matter where it is stored, whether in a data frame, a data table or database.

This package provides a unified interface to interact with Docker and Singularity containers. You can execute a command inside a container, mount a volume or copy a file.

Keep track of dates in terms of fractional calendar months per Damien Laker "Time Calculations for Annualizing Returns: the Need for Standardization", The Journal of Performance Measurement, 2008. Model dates as of close of business. Perform date arithmetic in units of "months" and "years". Allow "infinite" dates to model "ultimate" time.

This package provides basic infrastructure for linear test statistics and permutation inference in the framework of Strasser and Weber (1999).

Estimate generalized additive mixed models via a version of function gamm from the mgcv package, using the lme4 packagefor estimation.

This package provides tools to get text from images of text using Abbyy Cloud Optical Character Recognition (OCR) API. With abbyyyR, one can easily OCR images, barcodes, forms, documents with machine readable zones, e.g. passports and get the results in a variety of formats including plain text and XML. To learn more about the Abbyy OCR API, see http://ocrsdk.com/.

This package estimates the parameters in Dirichlet-Multinomial and computes log-likelihoods.

This package provides the means to compile user-supplied C++ functions with Rcpp and retrieve an XPtr that can be passed to other C++ components.

This package provides a dependency management toolkit for R. Using renv, you can create and manage project-local R libraries, save the state of these libraries to a lockfile, and later restore your library as required. Together, these tools can help make your projects more isolated, portable, and reproducible.