Scrapes football match shots data from Understat <https://understat.com/> and visualizes it using interactive plots: - A detailed shot map displaying the location, type, and xG value of shots taken by both teams. - An xG timeline chart showing the cumulative xG for each team over time, annotated with the details of scored goals.

Fit, summarize and plot sinusoidal hysteretic processes using: two-step simple harmonic least squares, ellipse-specific non-linear least squares, the direct method, geometric least squares or linear least squares. See Yang, F and A. Parkhurst, "Efficient Estimation of Elliptical Hysteresis with Application to the Characterization of Heat Stress" <DOI:10.1007/s13253-015-0213-6>.

Generates Rd files from R source code with comments. The main features of the default syntax are that (1) docs are defined in comments near the relevant code, (2) function argument names are not repeated in comments, and (3) examples are defined in R code, not comments. It is also easy to define a new syntax.

This package provides an l1-version of the spectral clustering algorithm devoted to robustly clustering highly perturbed graphs using l1-penalty. This algorithm is described with more details in the preprint C. Champion, M. Champion, M. Blazère, R. Burcelin and J.M. Loubes, "l1-spectral clustering algorithm: a spectral clustering method using l1-regularization" (2022).

Local explanations of machine learning models describe, how features contributed to a single prediction. This package implements an explanation method based on LIME (Local Interpretable Model-agnostic Explanations, see Tulio Ribeiro, Singh, Guestrin (2016) <doi:10.1145/2939672.2939778>) in which interpretable inputs are created based on local rather than global behaviour of each original feature.

Automates the process of creating a scale bar and north arrow in any package that uses base graphics to plot in R. Bounding box tools help find and manipulate extents. Finally, there is a function to automate the process of setting margins, plotting the map, scale bar, and north arrow, and resetting graphic parameters upon completion.

This package provides a collection of highly configurable, touch-enabled knob input controls for shiny'. These components can be styled to fit in perfectly in any app, and allow users to set precise values through many input modalities. Users can touch-and-drag, click-and-drag, scroll their mouse wheel, double click, or use keyboard input.

The tmap package provides two plotting modes for static and interactive thematic maps. This package extends tmap with two additional modes based on Mapbox GL JS and MapLibre GL JS'. These modes feature interactive vector tiles, globe views, and other modern web-mapping capabilities, while maintaining a consistent tmap interface across all plotting modes.

To handle higher-order tensor data. See Kolda and Bader (2009) <doi:10.1137/07070111X> for details on tensor. While existing packages on tensor data extend the base array class to some data classes, this package serves as an alternative resort to handle tensor only as array class. Some functionalities related to missingness are also supported.

This package provides functions to support economic modelling in R based on the methods of the Dutch guideline for economic evaluations in healthcare <https://www.zorginstituutnederland.nl/documenten/2024/01/16/richtlijn-voor-het-uitvoeren-van-economische-evaluaties-in-de-gezondheidszorg>, CBS data <https://www.cbs.nl/>, and OECD data <https://www.oecd.org/en.html>.

Fetch United States Congressional Records from their API <https://api.govinfo.gov/docs/> such as congressional speeches, speaker names, and metadata about congressional sessions, and detailed granule records. Optional parameters allow users to specify congressional sessions, and the maximum number of speeches to retrieve. Data is parsed, cleaned, and returned in a structured dataframe for analysis.

unicorn is an HTTP server for Rack applications designed to only serve fast clients on low-latency, high-bandwidth connections and take advantage of features in Unix/Unix-like kernels. Slow clients should only be served by placing a reverse proxy capable of fully buffering both the the request and response in between unicorn and slow clients.

The package is usable with Affymetrix GeneChip short oligonucleotide arrays, and it can be adapted or extended to other platforms. It is able to modify or replace the grouping of probes in the probe sets. Also, the package contains simple functions to read R connections in the FASTA format and it can create an alternative mapping from sequences.

HDCytoData contains a set of high-dimensional cytometry benchmark datasets. These datasets are formatted into SummarizedExperiment and flowSet Bioconductor object formats, including all required metadata. Row metadata includes sample IDs, group IDs, patient IDs, reference cell population or cluster labels and labels identifying spiked in cells. Column metadata includes channel names, protein marker names, and protein marker classes.

In order to smoothly animate the transformation of polygons and paths, many aspects needs to be taken into account, such as differing number of control points, changing center of rotation, etc. The transformr package provides an extensive framework for manipulating the shapes of polygons and paths and can be seen as the spatial brother to the tweenr package.

R's default conflict management system gives the most recently loaded package precedence. This can make it hard to detect conflicts, particularly when they arise because a package update creates ambiguity that did not previously exist. The conflicted package takes a different approach, making every conflict an error and forcing you to choose which function to use.

This package implements multitaper spectral estimation techniques using prolate spheroidal sequences (Slepians) and sine tapers for time series analysis. It includes an adaptive weighted multitaper spectral estimate, a coherence estimate, Thomson's Harmonic F-test, and complex demodulation. The Slepians sequences are generated efficiently using a tridiagonal matrix solution, and jackknifed confidence intervals are available for most estimates.

Random Jungle is an implementation of Random Forests. It is supposed to analyse high dimensional data. In genetics, it can be used for analysing big Genome Wide Association (GWA) data. Random Forests is a powerful machine learning method. Most interesting features are variable selection, missing value imputation, classifier creation, generalization error estimation and sample proximities between pairs of cases.

Mixedpower uses pilotdata and a linear mixed model fitted with lme4 to simulate new data sets. Power is computed separate for every effect in the model output as the relation of significant simulations to all simulations. More conservative simulations as a protection against a bias in the pilotdata are available as well as methods for plotting the results.

Detect binding sites using motifs IUPAC sequence or bed coordinates and ChIP-seq experiments in bed or bam format. Combine/compare binding sites across experiments, tissues, or conditions. All normalization and differential steps are done using TMM-GLM method. Signal decomposition is done by setting motifs as the centers of the mixture of normal distribution curves.

Package BHMSMAfMRI performs Bayesian hierarchical multi-subject multiscale analysis of fMRI data as described in Sanyal & Ferreira (2012) <DOI:10.1016/j.neuroimage.2012.08.041>, or other multiscale data, using wavelet-based prior that borrows strength across subjects and provides posterior smoothed images of the effect sizes and samples from the posterior distribution.

Climate crop zoning based in minimum and maximum air temperature. The data used in the package are from TerraClimate dataset (<https://www.climatologylab.org/terraclimate.html>), but, it have been calibrated with automatic weather stations of National Meteorological Institute of Brazil. The climate crop zoning of this package can be run for all the Brazilian territory.

Allows user to obtain subsets of columns of data or vectors within a list. These subsets will match the original data in terms of average and variation, but have a consistent length of data per column. It is intended for use on automated data generation which may not always output the same N per replicate or sample.

This package provides a comprehensive toolkit for scraping and analyzing book data from <https://www.goodreads.com/>. This package provides functions to search for books, scrape book details and reviews, perform sentiment analysis on reviews, and conduct topic modeling. It's designed for researchers, data analysts, and book enthusiasts who want to gain insights from Goodreads data.