Parses HTTP user agent strings and returns user agent, device and OS information. This is a â V8â -backed package that uses the UA, device and OS definitions from the â ua-parserâ project <https://github.com/ua-parser>.

Make requests from the US Treasury Fiscal Data API endpoints.

S3 classes and methods for manipulation with georeferenced raster data: reading/writing, processing, multi-panel visualization.

Basic statistical analyses. The package provides comprehensive functions and datasets for teaching introductory statistics courses. It has been developed to be used in undergraduate statistics courses at Bocconi University (Milan, Italy), and constitutes the core software tool used throughout the textbook by Piccarreta, R., Tonini, D., & Trentini, F. (2026) "From Data to Decisions. An Introduction to Applied Statistics", BUP, ISBN:9788823824096.

Density, distribution function, quantile function, and random generating function of the Unit-Garima distribution based on Ayuyuen, S., & Bodhisuwan, W. (2024)<doi:10.18187/pjsor.v20i1.4307>.

Fast flattening of hierarchical data structures (e.g. JSON, XML) into data.frames with a flexible spec language.

Pseudo-random number generation of 17 univariate distributions proposed by Demirtas. (2005) <DOI:10.22237/jmasm/1114907220>.

This package provides tools for analyzing sequencing data containing unique molecular identifiers generated by UMIErrorCorrect (<https://github.com/stahlberggroup/umierrorcorrect>).

Automatically converts language-specific verbal information, e.g., "1st half of the 19th century," to its standardized numerical counterparts, e.g., "1801-01-01/1850-12-31." It follows the recommendations of the MIDAS ('Marburger Informations-, Dokumentations- und Administrations-System'), see <doi:10.11588/artdok.00003770>.

This package provides functions for converting between UK and US spellings of English words.

For each string in a set of strings, determine a unique tag that is a substring of fixed size k unique to that string, if it has one. If no such unique substring exists, the least frequent substring is used. If multiple unique substrings exist, the lexicographically smallest substring is used. This lexicographically smallest substring of size k is called the "UniqTag" of that string.

Probability functions, family for glm() and Stan code for working with the unifed distribution (Quijano Xacur, 2019; <doi:10.1186/s40488-019-0102-6>).

Provide a set of wrappers to call all the endpoints of UptimeRobot API which includes various kind of ping, keep-alive and speed tests. See <https://uptimerobot.com/> for more information.

Create United Nations High Commissioner for Refugees (UNHCR) branded documents, presentations, and reports using R Markdown templates. This package provides customized formats that align with UNHCR's official brand guidelines for creating professional PDF reports, Word documents, PowerPoint presentations, and HTML outputs.

Generate, parse, and validate RFC 9562 UUIDs from R using the Rust uuid crate via extendr'. Developed by Thomas Bryce Kelly at Icy Seas Co-Laboratory LLC. Version 7 UUIDs are the default for new identifiers, while versions 4, 5, 6, and legacy version 1 are also supported. Functions return character vectors by default and can also expose 16-byte raw representations for low-level workflows.

This package provides functions to implement the methods of the Flood Estimation Handbook (FEH), associated updates and the revitalised flood hydrograph model (ReFH). Currently the package uses NRFA peak flow dataset version 15. Aside from FEH functionality, further hydrological functions are available. Most of the methods implemented in this package are described in one or more of the following: "Flood Estimation Handbook", Centre for Ecology & Hydrology (1999, ISBN:0 948540 94 X). "Flood Estimation Handbook Supplementary Report No. 1", Kjeldsen (2007, ISBN:0 903741 15 7). "Regional Frequency Analysis - an approach based on L-moments", Hosking & Wallis (1997, ISBN: 978 0 521 01940 8). "Making better use of local data in flood frequency estimation", Environment Agency (2017, ISBN: 978 1 84911 387 8). "Sampling uncertainty of UK design flood estimation" , Hammond (2021, <doi:10.2166/nh.2021.059>). "The FEH 2025 statistical method update", UK Centre for Ecology and Hydrology (2025). "Low flow estimation in the United Kingdom", Institute of Hydrology (1992, ISBN 0 948540 45 1). Data from the UK National River Flow Archive (<https://nrfa.ceh.ac.uk/>, terms and conditions: <https://nrfa.ceh.ac.uk/help/costs-terms-and-conditions>).

Three functions are provided: first function changes time from local to UTC, other changes from UTC to local and third returns difference between local and UTC. %h+% operator is also provided it adds hours to a time.

This package provides a tool for checking how much information is disclosed when reporting summary statistics.

This package performs parameter estimation using the Expectation-Maximization (EM) algorithm of Dempster, Laird, and Rubin (1977) <doi:10.1111/j.2517-6161.1977.tb01600.x> for arbitrary univariate probability distributions under numerous censoring and truncation schemes. Users supply the probability density function (PDF), cumulative distribution function (CDF), survival function, initial parameter vector, support bounds, and observed data; the package automatically estimates parameters using the EM algorithm under the specified censoring scheme. Supported schemes include complete data, right censoring, left censoring, interval censoring, random censoring, block random censoring, Type-I censoring, Type-II censoring, progressive Type-II censoring (Balakrishnan and Aggarwala (2000, ISBN:978-1-4612-1334-5)), progressive first failure censoring, joint Type-I censoring, joint Type-II censoring, balanced joint progressive Type-II censoring, hybrid censoring, hybrid Type-I censoring, hybrid Type-II censoring, Type-I hybrid censoring, Type-II progressively hybrid censoring, doubly Type-II censoring, middle censoring, right truncation, and left truncation. Standard errors are computed via the observed information matrix (numerical Hessian), the Louis (1982) <doi:10.1111/j.2517-6161.1982.tb01203.x> method, and the supplemented EM (SEM) algorithm of Meng and Rubin (1991) <doi:10.1080/01621459.1991.10475130>. The package also provides confidence intervals, model selection criteria (AIC, BIC, AICc, HQIC), goodness-of-fit statistics (Kolmogorov-Smirnov, Cramer-von Mises, Anderson-Darling), residual analysis (randomized quantile residuals, generalized residuals), parametric bootstrap methods, Aitken acceleration for convergence improvement, and comprehensive visualization tools. References: Wu and Kus (2009) <doi:10.1016/j.csda.2009.03.010>, Kundu and Joarder (2006) <doi:10.1016/j.csda.2005.05.002>, Iyer, Jammalamadaka, and Kundu (2008) <doi:10.1016/j.jspi.2007.03.062>, Banerjee and Kundu (2008) <doi:10.1109/TR.2008.916890>, Prajapati, Mitra, and Kundu (2019) <doi:10.1007/s13571-018-0167-0>, Mondal and Kundu (2020) <doi:10.1080/03610926.2018.1554128>, Ding and Gui (2023) <doi:10.3390/math11092003>.

This package provides functions for uniform sampling of the environmental space, designed to assist species distribution modellers in gathering ecologically relevant pseudo-absence data. The method ensures balanced representation of environmental conditions and helps reduce sampling bias in model calibration. Based on the framework described by Da Re et al. (2023) <doi:10.1111/2041-210X.14209>.

This package provides a classification (decision) tree is constructed from survival data with high-dimensional covariates. The method is a robust version of the logrank tree, where the variance is stabilized. The main function "uni.tree" returns a classification tree for a given survival dataset. The inner nodes (splitting criterion) are selected by minimizing the P-value of the two-sample the score tests. The decision of declaring terminal nodes (stopping criterion) is the P-value threshold given by an argument (specified by user). This tree construction algorithm is proposed by Emura et al. (2021, in review).

Wraps the unrtf utility <https://www.gnu.org/software/unrtf/> to extract text from RTF files. Supports document conversion to HTML, LaTeX or plain text. Output in HTML is recommended because unrtf has limited support for converting between character encodings.

Find and import datasets from the University of California Irvine Machine Learning (UCI ML) Repository into R. Supports working with data from UCI ML repository inside of R scripts, notebooks, and Quarto'/'RMarkdown documents. Access the UCI ML repository directly at <https://archive.ics.uci.edu/>.

Fit a univariate-guided sparse regression (lasso), by a two-stage procedure. The first stage fits p separate univariate models to the response. The second stage gives more weight to the more important univariate features, and preserves their signs. Conveniently, it returns an objects that inherits from class glmnet', so that all of the methods for glmnet are available. See Chatterjee, Hastie and Tibshirani (2025) <doi:10.1162/99608f92.c79ff6db> for details.