Standardizes and reconciles scientific plant names against a World Checklist of Vascular Plants ('WCVP')-style taxonomic backbone. The package parses names into taxonomic components and applies staged exact and fuzzy matching for binomial and trinomial inputs, including infraspecific rank-aware checks. It also returns accepted-name context and row-level matching flags to support reproducible, auditable preprocessing for downstream biodiversity, spatial, and trait analyses. A user-supplied backbone can be passed through target_df'; when the optional companion package wcvpdata is installed, its default checklist can also be used.

Use various regression models for the analysis of win loss endpoints adjusting for non-binary and multivariate covariates.

Tool-set of modules for creating web-based applications that use plot based strategies to visualize and analyze multi-omics data. This package utilizes the shiny and plotly frameworks to provide a user friendly dashboard for interactive plotting.

Computes exact observation weights for the Kalman filter and smoother, following Koopman and Harvey (2003) <www.sciencedirect.com/science/article/pii/S0165188902000611>. The package provides tools for analyzing linear Gaussian state-space models, allowing users to quantify the contribution of individual observations to filtered and smoothed state estimates. These weights can be used for interpretation, decomposition, and diagnostic analysis in time series models, including applications such as dynamic factor models. See the README for examples.

Treemaps are a visually appealing graphical representation of numerical data using a space-filling approach. A plane or map is subdivided into smaller areas called cells. The cells in the map are scaled according to an underlying metric which allows to grasp the hierarchical organization and relative importance of many objects at once. This package contains two different implementations of treemaps, Voronoi treemaps and Sunburst treemaps. The Voronoi treemap function subdivides the plot area in polygonal cells according to the highest hierarchical level, then continues to subdivide those parental cells on the next lower hierarchical level, and so on. The Sunburst treemap is a computationally less demanding treemap that does not require iterative refinement, but simply generates circle sectors that are sized according to predefined weights. The Voronoi tesselation is based on functions from Paul Murrell (2012) <https://www.stat.auckland.ac.nz/~paul/Reports/VoronoiTreemap/voronoiTreeMap.html>.

Run mixed-effects models that include weights at every level. The WeMix package fits a weighted mixed model, also known as a multilevel, mixed, or hierarchical linear model (HLM). The weights could be inverse selection probabilities, such as those developed for an education survey where schools are sampled probabilistically, and then students inside of those schools are sampled probabilistically. Although mixed-effects models are already available in R, WeMix is unique in implementing methods for mixed models using weights at multiple levels. Both linear and logit models are supported. Models may have up to three levels. Random effects are estimated using the PIRLS algorithm from lme4pureR (Walker and Bates (2013) <https://github.com/lme4/lme4pureR>).

Graphical data analysis of accelerated life tests. Methods derived from Wayne Nelson (1990, ISBN: 9780471522775), William Q. Meeker and Lois A. Escobar (1998, ISBN: 1-471-14328-6).

Simulates the results of completed randomized controlled trials, as if they had been conducted as adaptive Multi-Arm Bandit (MAB) trials instead. Augmented inverse probability weighted estimation (AIPW), outlined by Hadad et al. (2021) <doi:10.1073/pnas.2014602118>, is used to robustly estimate the probability of success for each treatment arm under the adaptive design. Provides customization options to simulate perfect/imperfect information, stationary/non-stationary bandits, blocked treatment assignments, along with control augmentation, and other hybrid strategies for assigning treatment arms. The methods used in simulation were inspired by Offer-Westort et al. (2021) <doi:10.1111/ajps.12597>.

Interface to the World Inequality Database (WID) API <https://wid.world>. Downloads distributional national accounts data with filters for country, year, percentile, age group, and population type. Includes code validation and reference tables. Independent implementation unaffiliated with the World Inequality Lab (WIL) or the Paris School of Economics.

Wavelet decomposition method is very useful for modelling noisy time series data. Wavelet decomposition using haar algorithm has been implemented to developed hybrid Wavelet GBM (Gradient Boosting Method) model for time series forecasting using algorithm by Anjoy and Paul (2017) <DOI:10.1007/s00521-017-3289-9>.

Enables interaction with the National Weather Service application programming web-interface for fetching of real-time and forecast meteorological data. Users can provide latitude and longitude, Automated Surface Observing System identifier, or Automated Weather Observing System identifier to fetch recent weather observations and recent forecasts for the given location or station. Additionally, auxiliary functions exist to identify stations nearest to a point, convert wind direction from character to degrees, and fetch active warnings. Results are returned as simple feature objects whenever possible.

The german Wikibook "GNU R" introduces R to new users. This package is a collection of functions and datas used in the german WikiBook "GNU R".

Collect multichannel marketing data from sources such as Google analytics, Facebook Ads, and many others using the Windsor.ai API <https://www.windsor.ai/api-fields/>.

Manage skills for large language model coding agents. Supports installing skills from GitHub or local directories, tracking versions in a lock file, and keeping installations current. Installations can be scoped to a single project or shared globally across projects.

Life data analysis in the graphical tradition of Waloddi Weibull. Methods derived from Robert B. Abernethy (2008, ISBN 0-965306-3-2), Wayne Nelson (1982, ISBN: 9780471094586), William Q. Meeker and Lois A. Escobar (1998, ISBN: 1-471-14328-6), John I. McCool, (2012, ISBN: 9781118217986).

Fast computation of Receiver Operating Characteristic (ROC) curves and Area Under the Curve (AUC) for weighted binary classification problems (weights are example-specific cost values).

This package provides functions for calculating the fetch (length of open water distance along given directions) and estimating wave energy from wind and wave monitoring data.

This package provides a large English words list and tools to find words by patterns. In particular, anagram finder and scrabble word finder.

This package provides API access to the Walmart Open API <https://developer.walmartlabs.com/>, that contains data about stores, Value of the day and products which includes names, sale prices, shipping rates and taxonomies.

This package provides methods for retrieving United States Geological Survey (USGS) water data using sequential and parallel processing (Bengtsson, 2022 <doi:10.32614/RJ-2021-048>). In addition to parallel methods, data wrangling and additional statistical attributes are provided.

Data from the United Nation's World Population Prospects 2010.

An R interface to the WebAIM WAVE accessibility evaluation API <https://wave.webaim.org/api/>. This package provides tools for analyzing web pages for accessibility issues, generating reports, and comparing accessibility across multiple websites.

This package provides functions for computing moments and coefficients related to the Beta-Wishart and Inverse Beta-Wishart distributions. It includes functions for calculating the expectation of matrix-valued functions of the Beta-Wishart distribution, coefficient matrices C_k and H_k, expectation of matrix-valued functions of the inverse Beta-Wishart distribution, and coefficient matrices \tildeC_k and \tildeH_k. For more details, refer Hillier and Kan (2024) <https://www-2.rotman.utoronto.ca/~kan/papers/wishmom.pdf>, "On the Expectations of Equivariant Matrix-valued Functions of Wishart and Inverse Wishart Matrices".

This package provides a powerful yet simple graphical tool available in the field of psychometrics is the Wright Map (also known as item maps or item-person maps), which presents the location of both respondents and items on the same scale. Wright Maps are commonly used to present the results of dichotomous or polytomous item response models. The WrightMap package provides functions to create these plots from item parameters and person estimates stored as R objects. Although the package can be used in conjunction with any software used to estimate the IRT model (e.g. TAM', mirt', eRm or IRToys in R', or Stata', Mplus', etc.), WrightMap features special integration with ConQuest to facilitate reading and plotting its output directly.The wrightMap function creates Wright Maps based on person estimates and item parameters produced by an item response analysis. The CQmodel function reads output files created using ConQuest software and creates a set of data frames for easy data manipulation, bundled in a CQmodel object. The wrightMap function can take a CQmodel object as input or it can be used to create Wright Maps directly from data frames of person and item parameters.