This package provides a set of R bindings for the Selenium 2.0 WebDriver (see https://selenium.dev/documentation/en/ for more information) using the JsonWireProtocol (see https://github.com/SeleniumHQ/selenium/wiki/JsonWireProtocol for more information). Selenium 2.0 WebDriver allows driving a web browser natively as a user would either locally or on a remote machine using the Selenium server it marks a leap forward in terms of web browser automation. Selenium automates web browsers (commonly referred to as browsers). Using RSelenium you can automate browsers locally or remotely.

Record asciicast screen casts from R scripts. Convert them to animated SVG images, to be used in README files, or blog posts. Includes asciinema-player as an HTML widget, and an asciicast knitr engine, to embed ascii screen casts in Rmarkdown documents.

This is a port of the WTC MATLAB package written by Aslak Grinsted and the wavelet program written by Christopher Torrence and Gibert P. Compo. This package can be used to perform univariate and bivariate (cross-wavelet, wavelet coherence, wavelet clustering) analyses.

Interface to a high-performance implementation of k-medoids clustering described in Tiwari, Zhang, Mayclin, Thrun, Piech and Shomorony (2020) "BanditPAM: Almost Linear Time k-medoids Clustering via Multi-Armed Bandits" <https://proceedings.neurips.cc/paper/2020/file/73b817090081cef1bca77232f4532c5d-Paper.pdf>.

Convolute probabilistic distributions using the random generator function of each distribution. A new random number generator function is created that perform the mathematical operation on the individual random samples from the random generator function of each distribution. See the documentation for examples.

Allows users to seamlessly query several CDC PLACES APIs (<https://data.cdc.gov/browse?q=PLACES%20&sortBy=relevance>) by geography, state, measure, and release year. This package also contains a function to explore the available measures for each release year.

Compute the certainty equivalents and premium risks as tools for risk-efficiency analysis. For more technical information, please refer to: Hardaker, Richardson, Lien, & Schumann (2004) <doi:10.1111/j.1467-8489.2004.00239.x>, and Richardson, & Outlaw (2008) <doi:10.2495/RISK080231>.

Rare variant association test integrating variant position information. It aims to identify the presence of clusters of disease-risk variants in specific gene regions. For more details, please read the publication from Persyn et al. (2017) <doi:10.1371/journal.pone.0179364>.

It enables detailed interpretation of complex classification and regression models through Shapley analysis including data-driven characterization of subgroups of individuals. Furthermore, it facilitates multi-measure model evaluation, model fairness, and decision curve analysis. Additionally, it offers enhanced visualizations with interactive elements.

This package implements Escalation With Overdose Control trial designs using two drug combinations described by this paper <doi:10.1002/sim.6961>(Tighiouart et al., 2016). It calculates the recommended dose for next cohorts and perform simulations to obtain operating characteristics.

Calculate cutoff values for model fit measures used in structural equation modeling (SEM) by simulating and testing data sets (cf. Hu & Bentler, 1999 <doi:10.1080/10705519909540118>) with the same parameters (population model, number of observations, etc.) as the model under consideration.

Measurement and partitioning of diversity, based on Tsallis entropy, following Marcon and Herault (2015) <doi:10.18637/jss.v067.i08>. entropart provides functions to calculate alpha, beta and gamma diversity of communities, including phylogenetic and functional diversity. Estimation-bias corrections are available.

The ggplot2 package provides simple functions for visualizing contours of 2-d kernel density estimates. ggdensity implements several additional density estimators as well as more interpretable visualizations based on highest density regions instead of the traditional height of the estimated density surface.

It performs maximum likelihood estimation for the Heckman selection model (Normal, Student-t or Contaminated normal) using an EM-algorithm <doi:10.1016/j.jmva.2021.104737>. It also performs influence diagnostic through global and local influence for four possible perturbation schema.

Haplotype and covariate relative risks in case-control data are estimated by weighted logistic regression. Diplotype probabilities, which are estimated by EM computation with progressive insertion of loci, are utilized as weights. French et al. (2006) <doi:10.1002/gepi.20161>.

The MetAlyzer S4 object provides methods to read and reformat metabolomics data for convenient data handling, statistics and downstream analysis. The resulting format corresponds to input data of the Shiny app MetaboExtract (<https://www.metaboextract.shiny.dkfz.de/MetaboExtract/>).

Three-dimensional rendering for grid and ggplot2 graphics using cubes and cuboids drawn with an oblique projection. As a special case also supports primary view orthographic projections. Can be viewed as an extension to the isocubes package <https://github.com/coolbutuseless/isocubes>.

Calculates seat allocation using the D-Hondt method, Sainte-Lague method, and Modified Sainte-Lague method, all commonly used in proportional representation electoral systems. For more information on these methods, see Michael Gallagher (1991)<doi:10.1016/0261-3794(91)90004-C>.

Fits classical sparse regression models with efficient active set algorithms by solving quadratic problems as described by Grandvalet, Chiquet and Ambroise (2017) <doi:10.48550/arXiv.1210.2077>. Also provides a few methods for model selection purpose (cross-validation, stability selection).

Create and train a multilayer perceptron, a type of feedforward, fully connected neural network. Features 2 ReLU hidden layers. Learn more about about the activation functions and backpropagation used by this network in Goodfellow et al. (2016, ISBN: 9780262035613) "Deep Learning".

Cluster analysis is one of the most fundamental problems in data science. We provide a variety of algorithms from clustering to the learning on the space of partitions. See Hennig, Meila, and Rocci (2016, ISBN:9781466551886) for general exposition to cluster analysis.

Unicodes are not friendly to work with, and not all Unicodes are Emoji per se, making obtaining Emoji statistics a difficult task. This tool can help your experience of working with Emoji as smooth as possible, as it has the tidyverse style.

Runs targets pipeline in /inst/tarchives and stores the results in the R user directory. This means that the user does not have to run the process repeatedly, and the developer has the flexibility to update the data as versions are updated.

This package provides tools for estimating vaccine effectiveness and related metrics. The vaccineff_data class manages key features for preparing, visualizing, and organizing cohort data, as well as estimating vaccine effectiveness. The results and model performance are assessed using the vaccineff class.