An interface to the Python package stanza <https://stanfordnlp.github.io/stanza/index.html>. stanza is a Python NLP library for many human languages. It contains support for running various accurate natural language processing tools on 60+ languages.

Sometimes it is useful to serve up alternative shiny UIs depending on information passed in the request object, such as the value of a cookie or a query parameter. This packages facilitates such switches.

Seeded Sequential LDA can classify sentences of texts into pre-define topics with a small number of seed words (Watanabe & Baturo, 2023) <doi:10.1177/08944393231178605>. Implements Seeded LDA (Lu et al., 2010) <doi:10.1109/ICDMW.2011.125> and Sequential LDA (Du et al., 2012) <doi:10.1007/s10115-011-0425-1> with the distributed LDA algorithm (Newman, et al., 2009) for parallel computing.

Data sets from Ramsey, F.L. and Schafer, D.W. (2013), "The Statistical Sleuth: A Course in Methods of Data Analysis (3rd ed)", Cengage Learning.

This package provides functions that compute the spatial covariance matrix for the matern and power classes of spatial models, for data that arise on rectangular units. This code can also be used for the change of support problem and for spatial data that arise on irregularly shaped regions like counties or zipcodes by laying a fine grid of rectangles and aggregating the integrals in a form of Riemann integration.

An R interface to the Python sqlfluff SQL linter and formatter via the reticulate package. Enables linting, fixing, and parsing of SQL queries with support for multiple dialects. Includes special handling for glue SQL syntax with curly-brace placeholders.

Efficient variational inference methods for fully Bayesian univariate and multivariate Gaussian and t-process regression models. Hierarchical shrinkage priors, including the triple gamma prior, are used for effective variable selection and covariance shrinkage in high-dimensional settings. The package leverages normalizing flows to approximate complex posterior distributions. For details on implementation, see Knaus (2025) <doi:10.48550/arXiv.2501.13173>.

Generate common data forms for complex data suitable for conversions and transmission by decomposition as paths or primitives. Paths are sequentially-linked records, primitives are basic atomic elements and both can model many forms and be grouped into hierarchical structures. The universal models SC0 (structural) and SC (labelled, relational) are composed of edges and can represent any hierarchical form. Specialist models PATH', ARC and TRI provide the most common intermediate forms used for converting from one form to another. The methods are inspired by the simplicial complex <https://en.wikipedia.org/wiki/Simplicial_complex> and provide intermediate forms that relate spatial data structures to this mathematical construct.

This package provides a combined slider and numeric input for usage in a Shiny app. The slider and the numeric input are linked together: each one is updated when the other one changes. Many styling properties are customizable (e.g. colors and size).

This package provides a collection of tools and functions to adjust a variety of stochastic blockmodels (SBM). Supports at the moment Simple, Bipartite, Multipartite and Multiplex SBM (undirected or directed with Bernoulli, Poisson or Gaussian emission laws on the edges, and possibly covariate for Simple and Bipartite SBM). See Léger (2016) <doi:10.48550/arXiv.1602.07587>, Barbillon et al. (2020) <doi:10.1111/rssa.12193> and Bar-Hen et al. (2020) <doi:10.48550/arXiv.1807.10138>.

This package provides tools for analyzing tail dependence in any sample or in particular theoretical models. The package uses only theoretical and non parametric methods, without inference. The primary goals of the package are to provide: (a)symmetric multivariate extreme value models in any dimension; theoretical and empirical indices to order tail dependence; theoretical and empirical graphical methods to visualize tail dependence.

This package provides functions for fitting Cliff-Ord-type spatial autoregressive models with and without heteroskedastic innovations using Generalized Method of Moments estimation are provided. Some support is available for fitting spatial HAC models, and for fitting with non-spatial endogeneous variables using instrumental variables.

High-performance spatial species accumulation curves using nearest-neighbor algorithms. Implements kNN and kNCN sampling methods with a C++ backend for speed. Supports Hill numbers (q=0,1,2), beta diversity partitioning (turnover/nestedness), coverage-based rarefaction and extrapolation, phylogenetic diversity (Faith's PD, mean pairwise distance, mean nearest taxon distance), functional diversity accumulation, diversity-area relationships (DAR), endemism-area curves, sampling-effort correction and fragmentation analysis, and species-area relationship (SAR) models based on extreme value theory (EVT). Multiple starting points (seeds) provide uncertainty quantification. Methods are described in Chao et al. (2014) <doi:10.1890/13-0133.1>, Baselga (2010) <doi:10.1111/j.1466-8238.2009.00490.x>, Chao and Jost (2012) <doi:10.1890/11-1952.1>, Faith (1992) <doi:10.1016/0006-3207(92)91201-3>, Ma (2018) <doi:10.1002/ece3.4526>, Borda-de-Agua et al. (2025) <doi:10.1038/s41467-025-59239-7>, Hanski et al. (2013) <doi:10.1073/pnas.1311190110>, and Jost (2007) <doi:10.1890/06-1736.1>.

This package provides a SAS interface, through SASPy'(<https://sassoftware.github.io/saspy/>) and reticulate'(<https://rstudio.github.io/reticulate/>). This package helps you create SAS sessions, execute SAS code in remote SAS servers, retrieve execution results and log, and exchange datasets between SAS and R'. It also helps you to install SASPy and create a configuration file for the connection. Please review the SASPy license file as instructed so that you comply with its separate and independent license.

Sample size estimation for bio-equivalence trials is supported through a simulation-based approach that extends the Two One-Sided Tests (TOST) procedure. The methodology provides flexibility in hypothesis testing, accommodates multiple treatment comparisons, and accounts for correlated endpoints. Users can model complex trial scenarios, including parallel and crossover designs, intra-subject variability, and different equivalence margins. Monte Carlo simulations enable accurate estimation of power and type I error rates, ensuring well-calibrated study designs. The statistical framework builds on established methods for equivalence testing and multiple hypothesis testing in bio-equivalence studies, as described in Schuirmann (1987) <doi:10.1007/BF01068419>, Mielke et al. (2018) <doi:10.1080/19466315.2017.1371071>, Shieh (2022) <doi:10.1371/journal.pone.0269128>, and Sozu et al. (2015) <doi:10.1007/978-3-319-22005-5>. Comprehensive documentation and vignettes guide users through implementation and interpretation of results.

Phenotypic analysis of field trials using mixed models with and without spatial components. One of a series of statistical genetic packages for streamlining the analysis of typical plant breeding experiments developed by Biometris. Some functions have been created to be used in conjunction with the R package asreml for the ASReml software, which can be obtained upon purchase from VSN international (<https://vsni.co.uk/software/asreml-r/>).

Package including functions and interactive shiny application for the psychometric analysis of educational tests, psychological assessments, health-related and other types of multi-item measurements, or ratings from multiple raters.

This gadget allows you to use the recipes package belonging to tidymodels to carry out the data preprocessing tasks in an interactive way. Build your recipe by dragging the variables, visually analyze your data to decide which steps to use, add those steps and preprocess your data.

This package provides tools for generating dynamic and standardized economic narratives in R Markdown documents. The package is primarily designed for French-language statistical and economic publications. It includes functions to describe changes in levels, percentages, trends, accelerations and short-term economic developments using consistent linguistic rules. The package supports automated reporting workflows and reproducible economic writing. Fournit des outils permettant de générer des textes économiques dynamiques et standardisés dans des documents R Markdown. Le package est principalement conçu pour les publications statistiques et économiques en français. Il propose des fonctions permettant de décrire les évolutions de niveaux, de pourcentages, de tendances, d'accélérations et les évolutions conjoncturelles à l'aide de règles linguistiques homogènes. Le package facilite l'automatisation de la rédaction et la reproductibilité des publications économiques.

This package provides functions for self-determination motivation theory (SDT) to compute measures of motivation internalization, motivation simplex structure, and of the original and adjusted self-determination or relative autonomy index. SDT was introduced by Deci and Ryan (1985) <doi:10.1007/978-1-4899-2271-7>. See package?SDT for an overview.

Calculation of solar zenith and azimuth angles.

This package provides R bindings for the Stencila Schema <https://schema.stenci.la>. This package is primarily aimed at R developers wanting to programmatically generate, or modify, executable documents.

This package provides a flexible tool for simulating complex longitudinal data using structural equations, with emphasis on problems in causal inference. Specify interventions and simulate from intervened data generating distributions. Define and evaluate treatment-specific means, the average treatment effects and coefficients from working marginal structural models. User interface designed to facilitate the conduct of transparent and reproducible simulation studies, and allows concise expression of complex functional dependencies for a large number of time-varying nodes. See the package vignette for more information, documentation and examples.

Facilitates basic and equation-based analyses of some important soil properties related to soil chemical environment and nutrient availability to plants. Freundlich H (1907). <doi:10.1515/zpch-1907-5723>. Datta SP, Bhadoria PBS (1999). <doi:10.1002%2F%28SICI%291522-2624%28199903%29162%3A2%3C183%3A%3AAID-JPLN183%3E3.0.CO%3B2-A>."Boron adsorption and desorption in some acid soils of West Bengal, India". Langmuir I (1918). <doi:10.1021/ja02242a004> "The adsorption of gases on plane surfaces of glass, mica, and platinum". Khasawneh FE (1971). <doi:10.2136/sssaj1971.03615995003500030029x> "Solution ion activity and plant growth".