This package contains functions to retrieve, organize, and visualize weather data from the NCEP/NCAR Reanalysis (<https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html>) and NCEP/DOE Reanalysis II (<https://psl.noaa.gov/data/gridded/data.ncep.reanalysis2.html>) datasets. Data are queried via the Internet and may be obtained for a specified spatial and temporal extent or interpolated to a point in space and time. We also provide functions to visualize these weather data on a map. There are also functions to simulate flight trajectories according to specified behavior using either NCEP wind data or data specified by the user.

Implementation of an algorithm in two steps to estimate parameters of a model whose latent dynamics are inferred through latent processes, jointly regularized. This package uses Monolix software (<https://monolixsuite.slp-software.com/>), which provide robust statistical method for non-linear mixed effects modeling. Monolix must have been installed prior to use.

This package provides a programmatic interface to web-services of YouTheria. YouTheria is an online database of mammalian trait data <http://www.utheria.org/>.

This package implements standard and reference based multiple imputation methods for continuous longitudinal endpoints (Gower-Page et al. (2022) <doi:10.21105/joss.04251>). In particular, this package supports deterministic conditional mean imputation and jackknifing as described in Wolbers et al. (2022) <doi:10.1002/pst.2234>, Bayesian multiple imputation as described in Carpenter et al. (2013) <doi:10.1080/10543406.2013.834911>, and bootstrapped maximum likelihood imputation as described in von Hippel and Bartlett (2021) <doi: 10.1214/20-STS793>.

Downloads, imports, and tidies time series data from the Australian Bureau of Statistics <https://www.abs.gov.au/>.

This package provides programmatic access to Glottography, an online repository of geospatial speaker-area polygons for the world's languages. The package allows users to list available datasets, download and install them, and load speaker-area polygons as standard spatial sf objects in R. Data are sourced from either the Glottography organization on GitHub <https://github.com/Glottography> or the Glottography community on Zenodo <https://zenodo.org/communities/glottography>. Based on Ranacher et al. (2026) <doi:10.5334/johd.459>.

This package provides functions to generate censored samples of type I, II and III, from any random sample generator. It also supplies the option to create left and right censorship. Along with this, the generation of samples with interval censoring is in the testing phase, with two options of fixed length intervals and random lengths.

Data for the vignette and examples in RFlocalfdr'. Contains a dataset of 1103547 importance values, and the table of variables used in the random forest splits. The data is Chromosome 22 taken from Auton et al. (2015) <doi:10.1038/nature15393>. It also contains a 51 samples by 22283 genes data set taken from Spira et al. (2004) <doi:10.1165/rcmb.2004-0273OC>.

Inference for the treatment effect with possibly invalid instrumental variables via TSHT ('Guo et al. (2018) <doi:10.1111/rssb.12275>) and SearchingSampling ('Guo (2023) <doi:10.1093/jrsssb/qkad049>), which are effective for both low- and high-dimensional covariates and instrumental variables; test of endogeneity in high dimensions ('Guo et al. (2018) <doi:10.1016/j.jeconom.2018.07.002>).

Frequentist sequential meta-analysis based on Trial Sequential Analysis (TSA) in programmed in Java by the Copenhagen Trial Unit (CTU). The primary function is the calculation of group sequential designs for meta-analysis to be used for planning and analysis of both prospective and retrospective sequential meta-analyses to preserve type-I-error control under sequential testing. RTSA includes tools for sample size and trial size calculation for meta-analysis and core meta-analyses methods such as fixed-effect and random-effects models and forest plots. TSA is described in Wetterslev et. al (2008) <doi:10.1016/j.jclinepi.2007.03.013>. The methods for deriving the group sequential designs are based on Jennison and Turnbull (1999, ISBN:9780849303166).

This package provides a client library for The Guardian (https://www.guardian.com/) and their API, this package allows users to search for Guardian articles and retrieve both the content and metadata.

Interface for multiple data sources, such as the `EDDS` API <https://evds2.tcmb.gov.tr/index.php?/evds/userDocs> of the Central Bank of the Republic of Türkiye and the `FRED` API <https://fred.stlouisfed.org/docs/api/fred/> of the Federal Reserve Bank. Both data providers require API keys for access, which users can easily obtain by creating accounts on their respective websites. The package provides caching ability with the selection of periods to increase the speed and efficiency of requests. It combines datasets requested from different sources, helping users when the data has common frequencies. While combining data frames whenever possible, it also keeps all requested data available as separate data frames to increase efficiency.

Creating 3D radial visualizations of multivariate data. The package extends traditional radial coordinate visualization (RadViz) techniques to three-dimensional space, enabling enhanced exploration and analysis of high-dimensional datasets through interactive 3D plots. Zhu, Dai & Maitra (2022) <doi:10.1080/10618600.2021.2020129>.

Perform sigmoidal Emax model fit using Stan in a formula notation, without writing Stan model code.

Analysis of DNA mixtures involving relatives by computation of likelihood ratios that account for dropout and drop-in, mutations, silent alleles and population substructure. This is useful in kinship cases, like non-invasive prenatal paternity testing, where deductions about individuals relationships rely on DNA mixtures, and in criminal cases where the contributors to a mixed DNA stain may be related. Relationships are represented by pedigrees and can include kinship between more than two individuals. The main function is relMix() and its graphical user interface relMixGUI(). The implementation and method is described in Dorum et al. (2017) <doi:10.1007/s00414-016-1526-x>, Hernandis et al. (2019) <doi:10.1016/j.fsigss.2019.09.085> and Kaur et al. (2016) <doi:10.1007/s00414-015-1276-1>.

This package provides an I/O interface between R data.frames and Raven DataFrames. Defines functions to both read and write DataFrame files, as well as serialize/deserialize data.frames/DataFrames.

Allows caching of raw data directly in R code. This allows R scripts and R Notebooks to be shared and re-run on a machine without access to the original data. Cached data is encoded into an ASCII string that can be pasted into R code. When the code is run, the data is automatically loaded from the cached version if the original data file is unavailable. Works best for small datasets (a few hundred observations).

An algorithm is proposed to estimate regression kink model proposed by the paper, Lixiong Yang and Jen-Je Su (2018) <doi:10.1016/j.jimonfin.2018.06.002>.

The Bayesian modelling of relative sea-level data using a comprehensive approach that incorporates various statistical models within a unifying framework. Details regarding each statistical models; linear regression (Ashe et al 2019) <doi:10.1016/j.quascirev.2018.10.032>, change point models (Cahill et al 2015) <doi:10.1088/1748-9326/10/8/084002>, integrated Gaussian process models (Cahill et al 2015) <doi:10.1214/15-AOAS824>, temporal splines (Upton et al 2025) <doi:10.32614/RJ-2024-018>, spatio-temporal splines (Upton et al 2025) <doi:10.32614/RJ-2024-018> and generalised additive models (Upton et al 2025) <doi:10.1093/jrsssc/qlae044>. This package facilitates data loading, model fitting and result summarisation. Notably, it accommodates the inherent measurement errors found in relative sea-level data across multiple dimensions, allowing for their inclusion in the statistical models.

Sets a significance level for Random Forest MDI (Mean Decrease in Impurity, Gini or sum of squares) variable importance scores, using an empirical Bayes approach. See Dunne et al. (2022) <doi:10.1101/2022.04.06.487300>.

Uses an indirect method based on truncated quantile-quantile plots to estimate reference limits from routine laboratory data: Georg Hoffmann and colleagues (2024) <doi: 10.3390/jcm13154397>. The principle of the method was developed by Robert G Hoffmann (1963) <doi:10.1001/jama.1963.03060110068020> and modified by Georg Hoffmann and colleagues (2015) <doi:10.1515/labmed-2015-0104>, and Frank Klawonn and colleagues (2020) <doi:10.1515/labmed-2020-0005>, (2022) <doi:10.1007/978-3-031-15509-3_31>.

Create and combine HTML and PDF reports from within R. Possibility to design tables and listings for reporting and also include R plots.

Combine multiple data files from a common directory. The data files will be read into R and bound together, creating a single large data.frame. A general function is provided along with a specific function for data that was collected using the open-source experiment builder OpenSesame <https://osdoc.cogsci.nl/>.

This package provides a collection of small text corpora of interesting data. It contains all data sets from dariusk/corpora'. Some examples: names of animals: birds, dinosaurs, dogs; foods: beer categories, pizza toppings; geography: English towns, rivers, oceans; humans: authors, US presidents, occupations; science: elements, planets; words: adjectives, verbs, proverbs, US president quotes.