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Additional Binary Operators
A set of binary operators for common tasks such as regex manipulation.
An R Interface to the Onigmo Regular Expression Library
Provides an alternative to R's built-in functionality for handling regular expressions, based on the Onigmo library. Offers first-class compiled regex objects, partial matching and function-based substitutions, amongst other features.
Match and Replace Strings Based on Named Groups in Regular Expressions
An R6 class "Replacer" provided by the package simplifies working with regex patterns containing named groups. It allows easy retrieval of matched portions and targeted replacements by group name, improving both code clarity and maintainability.
A Lightweight and Versatile NLP Toolkit
A toolkit for web scraping, modular NLP pipelines, and text preparation for large language models. Organized around four core actions: fetching, reading, processing, and searching. Covers the full pipeline from raw web data acquisition to structural text processing and BM25 indexing. Supports multiple retrieval strategies including regex, dictionary matching, and ranked keyword search. Pipe-friendly with no heavy dependencies; all outputs are plain data frames or data.tables.
Universal Messy Panel Data Cleaner
A robust toolkit designed to standardize and clean complex tabular data
from commercial enterprise systems, healthcare records, logistics software, and HR
databases. Features include intelligent regex parsing for domain-specific noise
(currencies, percentages), gap-based block clustering, and automated messy table
resolution. Methods draw on tidy data principles described in Wickham (2014)
R6 Objects for Text and Data
For natural language processing and analysis of qualitative text coding structures which provide a way to bind together text and text data are fundamental. The package provides such a structure and accompanying methods in form of R6 objects. The 'rtext' class allows for text handling and text coding (character or regex based) including data updates on text transformations as well as aggregation on various levels. Furthermore, the usage of R6 enables inheritance and passing by reference which should enable 'rtext' instances to be used as back-end for R based graphical text editors or text coding GUIs.
Download Online Imagery Tiles
Download imagery tiles to a standard cache and load the data into raster objects. Facilities for 'AWS' terrain < https://registry.opendata.aws/terrain-tiles/> terrain and 'Mapbox' < https://www.mapbox.com/> servers are provided.
Linear Latent Non-Gaussian Models with Flexible Distributions
Fits and analyzes linear latent non-Gaussian models for
temporal, spatial, and space-time data. The package provides model
components for autoregressive and Ornstein-Uhlenbeck processes, random
walks, Matern fields based on stochastic partial differential equations,
separable and non-separable space-time models, graph-based Matern models,
bivariate type-G fields, and user-defined sparse operators. Latent fields
and observation models can use Gaussian and non-Gaussian noise
distributions, including normal inverse Gaussian, generalized asymmetric
Laplace, and skew-t distributions. Functions are included for simulation,
likelihood-based estimation, prediction, cross-validation, convergence
diagnostics, stochastic gradient optimization, batch-means confidence
intervals, and posterior-like sampling. The modeling framework is described
in Bolin, Jin, Simas and Wallin (2026) "A Unified and Computationally
Efficient Non-Gaussian Statistical Modeling Framework"
Core Functionality for the 'rebus' Package
Build regular expressions piece by piece using human readable code. This package contains core functionality, and is primarily intended to be used by package developers.
Build Regular Expressions in a Human Readable Way
Build regular expressions piece by piece using human readable code. This package is designed for interactive use. For package development, use the rebus.* dependencies.