This package provides system native access to the font catalogue. As font handling varies between systems it is difficult to correctly locate installed fonts across different operating systems. The 'systemfonts' package provides bindings to the native libraries for finding font files that can then be used further by e.g. graphic devices.

This package contains an implementation of a high-quality splittable pseudorandom number generator. The generator is based on a cryptographic hash function built on top of the ThreeFish block cipher. See the paper "Splittable Pseudorandom Number Generators Using Cryptographic Hashing" by Claessen, Pałka for details and the rationale of the design.

Package for the access and distribution of Long-term lake datasets from lakes in the Adirondack Park, northern New York state. Includes a wide variety of physical, chemical, and biological parameters from 28 lakes. Data are from multiple collection organizations and have been harmonized in both time and space for ease of reuse.

Lite interface for finding locations of addresses or businesses around the world using the ArcGIS REST API service <https://developers.arcgis.com/rest/geocode/api-reference/overview-world-geocoding-service.htm>. Address text can be converted to location candidates and a location can be converted into an address. No API key required.

This package implements a bootstrap aggregated (bagged) version of the k-nearest neighbors survival probability prediction method (Lowsky et al. 2013). In addition to the bootstrapping of training samples, the features can be subsampled in each baselearner to break the correlation between them. The Rcpp package is used to speed up the computation.

Hospital machine learning and ai data analysis workflow tools, modeling, and automations. This library provides many useful tools to review common administrative hospital data. Some of these include predicting length of stay, and readmits. The aim is to provide a simple and consistent verb framework that takes the guesswork out of everything.

Turning point method is a method proposed by Choi (1990) <doi:10.2307/2531453> to estimate 50 percent effective dose (ED50) in the study of drug sensitivity. The method has its own advantages for that it can provide robust ED50 estimation. This package contains the modified function of Choi's turning point method.

Mine metrics on common places on the web through the power of their APIs (application programming interfaces). It also helps make the data in a format that is easily used for a dashboard or other purposes. There is an associated dashboard template and tutorials that are underdevelopment that help you fully utilize metricminer'.

Data is synthesized using a combination of inverse transform sampling using the empirical quantile functions for each variable, and then copying the rank order structure from the original dataset. The syntesizer method has a tunable parameter allowing to gradually move from realistic and possibly unsafe synthetic data to decorrelated data of less utility.

deMULTIplex is an R package for analyzing single-cell RNA sequencing data generated with the MULTI-seq sample multiplexing method. The package includes software to

1. Convert raw MULTI-seq sample barcode library FASTQs into a sample barcode UMI count matrix, and

2. Classify cell barcodes into sample barcode groups.

This package provides functions, documentation and example data to help divide geographic space into discrete polygons (zones). The functions are motivated by research into the merits of different zoning systems. A flexible ClockBoard zoning system is provided, which breaks-up space by concentric rings and radial lines emanating from a central point.

This package only contains and exports a single function realdot(x, y). It computes real(LinearAlgebra.dot(x, y)) while avoiding computing the imaginary part of LinearAlgebra.dot(x, y) if possible. The real dot product is useful when one treats complex numbers as embedded in a real vector space.

Ref::Util introduces several functions to help identify references in a smarter (and usually faster) way. The difference with conventional approach:

• No comparison against a string constant

• Supports blessed variables

• Supports tied variables and magic

• Ignores overloading

• Ignores subtle types

• Usually faster

Various tools for inferring causal models from observational data. The package includes an implementation of the temporal Peter-Clark (TPC) algorithm. Petersen, Osler and Ekstrøm (2021) <doi:10.1093/aje/kwab087>. It also includes general tools for evaluating differences in adjacency matrices, which can be used for evaluating performance of causal discovery procedures.

This package creates the "table one" of bio-medical papers. Fill it with your data and the name of the variable which you'll make the group(s) out of and it will make univariate, bivariate analysis and parse it into HTML. It also allows you to visualize all your data with graphic representation.

This package provides tools to compute the neural fragility matrix from intracranial electrocorticographic (iEEG) recordings, enabling the analysis of brain dynamics during seizures. The package implements the method described by Li et al. (2017) <doi:10.23919/ACC.2017.7963378> and includes functions for data preprocessing (`Epoch`), fragility computation (`calcAdjFrag`), and visualization.

Offers a set of functions to easily download and clean Brazilian electoral data from the Superior Electoral Court and CepespData websites. Among other features, the package retrieves data on local and federal elections for all positions (city councilor, mayor, state deputy, federal deputy, governor, and president) aggregated by state, city, and electoral zones.

Allows users to fit a cosinor model using the glmmTMB framework. This extends on existing cosinor modeling packages, including cosinor and circacompare', by including a wide range of available link functions and the capability to fit mixed models. The cosinor model is described by Cornelissen (2014) <doi:10.1186/1742-4682-11-16>.

Hospital time series data analysis workflow tools, modeling, and automations. This library provides many useful tools to review common administrative time series hospital data. Some of these include average length of stay, and readmission rates. The aim is to provide a simple and consistent verb framework that takes the guesswork out of everything.

This package provides a collection of Irucka Embry's miscellaneous USGS data sets (USGS Parameter codes with fixed values, USGS global time zone codes, and US Air Force Global Engineering Weather Data). Irucka created these data sets while a Cherokee Nation Technology Solutions (CNTS) United States Geological Survey (USGS) Contractor and/or USGS employee.

This package provides a collection of functions for sensitivity analysis of model outputs (factor screening, global sensitivity analysis and robustness analysis), for variable importance measures of data, as well as for interpretability of machine learning models. Most of the functions have to be applied on scalar output, but several functions support multi-dimensional outputs.

Read General Transit Feed Specification (GTFS) zipfiles into a list of R dataframes. Perform validation of the data structure against the specification. Analyze the headways and frequencies at routes and stops. Create maps and perform spatial analysis on the routes and stops. Please see the GTFS documentation here for more detail: <https://gtfs.org/>.

This package is a comprehensive visualization tool specifically designed for exploring phylomorphospace. It not only simplifies the process of generating phylomorphospace, but also enhances it with the capability to add graphic layers to the plot with grammar of graphics to create fully annotated phylomorphospaces. It also provide some utilities to help interpret evolutionary patterns.

immunoClust is a model based clustering approach for Flow Cytometry samples. The cell-events of single Flow Cytometry samples are modelled by a mixture of multinominal normal- or t-distributions. The cell-event clusters of several samples are modelled by a mixture of multinominal normal-distributions aiming stable co-clusters across these samples.