This package provides miscellaneous functions for training and plotting classification and regression models.

This package contains miscellaneous functions used to interpret and translate, factorize and negate Sum of Products expressions, for both binary and multi-value crisp sets, and to extract information (set names, set values) from those expressions. Other functions perform various other checks if possibly numeric (even if all numbers reside in a character vector) and coerce to numeric, or check if the numbers are whole. It also offers, among many others, a highly flexible recoding routine and a more flexible alternative to the base function with().

Streaming JSON (ndjson) has one JSON record per-line and many modern ndjson files contain large numbers of records. These constructs may not be columnar in nature, but it is often useful to read in these files and "flatten" the structure out to enable working with the data in an R data.frame-like context. Functions are provided that make it possible to read in plain ndjson files or compressed (gz) ndjson files and either validate the format of the records or create "flat" data.table structures from them.

This package lets you easily use Bootstrap icons inside Shiny apps and R Markdown documents. More generally, icons can be inserted in any htmltools document through inline SVG.

This is a package for fast and user-friendly estimation of econometric models with multiple fixed-effects. It includes ordinary least squares (OLS), generalized linear models (GLM) and the negative binomial. The core of the package is based on optimized parallel C++ code, scaling especially well for large data sets. The method to obtain the fixed-effects coefficients is based on Berge (2018). It further provides tools to export and view the results of several estimations with intuitive design to cluster the standard-errors.

Constructs confidence intervals on the probability of success in a binomial experiment via several parameterizations

This package can be used to predict the r-species accumulation curve (r-SAC), which is the number of species represented at least r times as a function of the sampling effort. When r = 1, the curve is known as the species accumulation curve, or the library complexity curve in high-throughput genomic sequencing. The package includes both parametric and nonparametric methods, as described by Deng C, et al. (2018).

This package provides the ggplot binning layer stat_summaries_hex(), which functions similar to its singular form, but allows the use of multiple statistics per bin. Those statistics can be mapped to multiple bin aesthetics.

This package provides functions to make zebra-striped tables (tables with alternating row colors) in LaTeX and HTML formats easily from data.frame, matrix, lm, aov, anova, glm, coxph, nls, fitdistr, mytable and cbind.mytable objects.

This package provides an R interface to the nanoarrow C library and the Apache Arrow application binary interface. Functions to import and export ArrowArray, ArrowSchema, and ArrowArrayStream C structures to and from R objects are provided alongside helpers to facilitate zero-copy data transfer among R bindings to libraries implementing the Arrow C data interface.

This package offers a flexible, feature-rich yet light-weight logging framework based on R6 classes. It supports hierarchical loggers, custom log levels, arbitrary data fields in log events, logging to plaintext, JSON, (rotating) files, memory buffers, and databases, as well as email and push notifications.

This package provides distance-based parametric bootstrap tests for clustering with spatial neighborhood information. It implements some distance measures, clustering of presence-absence, abundance and multilocus genetical data for species delimitation, nearest neighbor based noise detection.

In computationally demanding analysis projects, statisticians and data scientists asynchronously deploy long-running tasks to distributed systems, ranging from traditional clusters to cloud services. The NNG-powered mirai R package by Gao (2023) <doi:10.5281/zenodo.7912722> is a scheduler that efficiently processes these intense workloads. The crew package extends mirai with a unifying interface for third-party worker launchers.

This package contains several basic utility functions including: moving (rolling, running) window statistic functions, read/write for GIF and ENVI binary files, fast calculation of AUC, LogitBoost classifier, base64 encoder/decoder, round-off-error-free sum and cumsum, etc.

This package provides functions to handle basic input output. These functions always read and write UTF-8 (8-bit Unicode Transformation Format) files and provide more explicit control over line endings.

This package provides the functionality to set configuration options on a per-package basis. Options set by a given package only apply to that package, other packages are unaffected.

This package provides a collection of functions to implement a class for univariate polynomial manipulations.

This package provides interactive visualizations for profiling R code.

This package is a collection of tools to load R packages and automatically generate BibTeX files citing them as well as load and cache plain-text and Excel formatted data stored on GitHub, and from other sources.

This package provides methods for enhanced visualization and interaction with raster data. It implements visualization methods for quantitative data and categorical data, both for univariate and multivariate rasters. It also provides methods to display spatiotemporal rasters, and vector fields.

This is a subset of the spatstat package, containing its functionality for spatial data on a linear network.

Generalized Additive Mixed Modeling (GAMM; Lin & Zhang, 1999) as implemented in the R package mgcv is a nonlinear regression analysis which is particularly useful for time course data such as EEG, pupil dilation, gaze data (eye tracking), and articulography recordings, but also for behavioral data such as reaction times and response data. As time course measures are sensitive to autocorrelation problems, GAMMs implements methods to reduce the autocorrelation problems. This package includes functions for the evaluation of GAMM models (e.g., model comparisons, determining regions of significance, inspection of autocorrelational structure in residuals) and interpreting of GAMMs (e.g., visualization of complex interactions, and contrasts).

This package provides functions to compute quasi variances and associated measures of approximation error.

This package provides utilities for secure password hashing via the argon2 algorithm.