Interface to TensorFlow <https://www.tensorflow.org/>, an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API'. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.

Easy visualization, wrangling, and feature engineering of time series data for forecasting and machine learning prediction. Consolidates and extends time series functionality from packages including dplyr', stats', xts', forecast', slider', padr', recipes', and rsample'.

Third order response surface designs (M. Hemavathi, Shashi Shekhar, Eldho Varghese, Seema Jaggi, Bikas Sinha & Nripes Kumar Mandal (2022) <DOI:10.1080/03610926.2021.1944213>."Theoretical developments in response surface designs: an informative review and further thoughts") are classified into two types viz., designs which are suitable for sequential experimentation and designs for non-sequential experimentation (M. Hemavathi, Eldho Varghese, Shashi Shekhar & Seema Jaggi (2022)<DOI:10.1080/02664763.2020.1864817>." Sequential asymmetric third order rotatable designs (SATORDs)"). The sequential experimentation approach involves conducting the trials step by step whereas, in the non-sequential experimentation approach, the entire runs are executed in one go.This package contains functions named STORDs() and NSTORDs() for generating sequential/non-sequential TORDs given in Das, M. N., and V. L. Narasimham (1962). <DOI:10.1214/aoms/1177704374>. "Construction of rotatable designs through balanced incomplete block designs" along with the randomized layout. It also contains another function named Pred3.var() for generating the variance of predicted response as well as the moment matrix based on a third order response surface model.

Assists performing tip-dating of phylogenetic trees with BEAST BEAST is a popular software for phylogenetic analysis. The package assists the implementation of various phylogenetic tip- dating tests using BEAST. It contains two main functions. The first one allows preparing date randomization analyses, which assess the temporal signal of a data set. The second function allows performing leave-one-out analyses, which test for the consistency between independent calibration sequences and allow pinpointing those leading to potential bias. The included tutorial provides detailed step-by-step instructions. An expanded description of the package can be found in article: Rieux, A. and Khatchikian, C.E. (2017), TIPDATINGBEAST: an R package to assist the implementation of phylogenetic tip-dating tests using BEAST. Molecular Ecology Resources, 17: 608-613. <onlinelibrary.wiley.com/doi/full/10.1111/1755-0998.12603>.

Defines the classes used to identify outliers (threshing) and compute the number of significant principal components and number of clusters (reaping) in a joint application of PCA and hierarchical clustering. See Wang et al., 2018, <doi:10.1186/s12859-017-1998-9>.

This package provides a lightweight and focused text annotation tool built with shiny'. Provides an interactive graphical user interface for coding text documents, managing code hierarchies, creating memos, and analyzing coding patterns. Features include code co-occurrence analysis, visualization of coding patterns, comparison of multiple coding sets, and export capabilities. Supports collaborative qualitative research through standardized annotation formats and analysis tools.

Extends the test-based Bayes factor (TBF) methodology to multinomial regression models and discrete time-to-event models with competing risks. The TBF methodology has been well developed and implemented for the generalised linear model [Held et al. (2015) <doi:10.1214/14-STS510>] and for the Cox model [Held et al. (2016) <doi:10.1002/sim.7089>].

Includes functions for mapping named lists to function arguments, random strings, pasting and combining rows together across columns, etc.

Trusted Timestamps (tts) are created by incorporating a hash of a file or dataset into a transaction on the decentralized blockchain (Stellar network). The package makes use of a free service provided by <https://stellarapi.io>.

Characterisation of the extremal dependence structure of time series, avoiding pre-processing and filtering as done typically with peaks-over-threshold methods. It uses the conditional approach of Heffernan and Tawn (2004) <DOI:10.1111/j.1467-9868.2004.02050.x> which is very flexible in terms of extremal and asymptotic dependence structures, and Bayesian methods improve efficiency and allow for deriving measures of uncertainty. For example, the extremal index, related to the size of clusters in time, can be estimated and samples from its posterior distribution obtained.

Optimize and compress images using Rust libraries to reduce file sizes while maintaining image quality. Supports PNG palette reduction and dithering via the exoquant crate before lossless PNG optimization via the oxipng crate. The package provides functions to optimize individual image files or entire directories, with configurable compression levels.

U.S. Department of the Treasury, Alcohol and Tobacco Tax and Trade Bureau (TTB) collects data and reports on monthly beer industry production and operations. This data package includes a collection of 10 years (2006 - 2015) worth of data on materials used at U.S. breweries in pounds reported by the Brewer's Report of Operations and the Quarterly Brewer's Report of Operations forms, ready for data analysis. This package also includes historical tax rates on distilled spirits, wine, beer, champagne, and tobacco products as individual data sets.

Better looking call stacks after an error.

First - Generates (potentially high-dimensional) high-frequency and low-frequency series for simulation studies in temporal disaggregation; Second - a toolkit utilizing temporal disaggregation and benchmarking techniques with a low-dimensional matrix of indicator series previously proposed in Dagum and Cholette (2006, ISBN:978-0-387-35439-2) ; and Third - novel techniques proposed by Mosley, Gibberd and Eckley (2021) <arXiv:2108.05783> for disaggregating low-frequency series in the presence of high-dimensional indicator matrices.

This queue is a data structure that lets parallel processes send and receive messages, and it can help coordinate the work of complicated parallel tasks. Processes can push new messages to the queue, pop old messages, and obtain a log of all the messages ever pushed. File locking preserves the integrity of the data even when multiple processes access the queue simultaneously.

This package provides a tm Source to create corpora from articles exported from the Dow Jones Factiva content provider as XML or HTML files. It is able to read both text content and meta-data information (including source, date, title, author, subject, geographical coverage, company, industry, and various provider-specific fields).

Unsupervised text tokenizer focused on computational efficiency. Wraps the YouTokenToMe library <https://github.com/VKCOM/YouTokenToMe> which is an implementation of fast Byte Pair Encoding (BPE) <https://aclanthology.org/P16-1162/>.

Gene and exon information from Ensembl genome builds GRCh38.p13 (104) and GRCh37 (v40) to use with the topr package.

This package provides a constrained two-dimensional Delaunay triangulation package providing both triangulation and generation of voronoi mosaics of irregular spaced data. Please note that most of the functions are now also covered in package interp, which is a re-implementation from scratch under a free license based on a different triangulation algorithm.

We provide a tidy grammar of population genetics, facilitating the manipulation and analysis of data on biallelic single nucleotide polymorphisms (SNPs). tidypopgen scales to very large genetic datasets by storing genotypes on disk, and performing operations on them in chunks, without ever loading all data in memory. The full functionalities of the package are described in Carter et al. (2025) <doi:10.1111/2041-210x.70204>.

Key-value store, implemented as a wrapper around LMDB'; the "lightning memory-mapped database" <https://www.symas.com/mdb>. LMDB is a transactional key value store that uses a memory map for efficient access. This package wraps the entire LMDB interface (except duplicated keys), and provides objects for transactions and cursors.

Collection of functions that allow to export data frames to excel workbook.

Flexible simulation of time series using time series components, including seasonal, calendar and outlier effects. Main algorithm described in Ollech, D. (2021) <doi:10.1515/jtse-2020-0028>.

This package provides a kernel of functions for programming time series methods in a way that is relatively independently of the representation of time. Also provides plotting, time windowing, and some other utility functions which are specifically intended for time series. See the Guide distributed as a vignette, or ?tframe.Intro for more details. (User utilities are in package tfplot.).