The COVID Symptom Study is a non-commercial project that uses a free mobile app to facilitate real-time data collection of symptoms, exposures, and risk factors related to COVID19. The package allows easy access to summary statistics data from COVID Symptom Study Sweden.

Helper functions for descriptive tasks such as making print-friendly bivariate tables, sample size flow counts, and visualizing sample distributions. Also contains R approximations of some common SAS and Stata functions such as PROC MEANS from SAS and ladder', gladder', and pwcorr from Stata'.

This package provides a suite of tools to allow you to download all publicly available parasite rate survey points, mosquito occurrence points and raster surfaces from the Malaria Atlas Project <https://malariaatlas.org/> servers as well as utility functions for plotting the downloaded data.

Flexible implementation of a structural change point detection algorithm for multivariate time series. It authorizes inclusion of trends, exogenous variables, and break test on the intercept or on the full vector autoregression system. Bai, Lumsdaine, and Stock (1998) <doi:10.1111/1467-937X.00051>.

Transactions occurring for a UK-based and registered, non-store online retail between 01/12/2010 and 09/12/2011 (Chen et. al., 2012, <doi:10.1145/1835804.1835882>). This dataset is included in this package with the donor's permission, Dr. Daqing Chen.

This package provides function for performing Bayesian survival regression using Horseshoe prior in the accelerated failure time model with log normal assumption in order to achieve high dimensional pan-cancer variable selection as developed in Maity et. al. (2019) <doi:10.1111/biom.13132>.

This package provides delayed computation of a matrix of scaled and centered values. The result is equivalent to using the scale function but avoids explicit realization of a dense matrix during block processing. This permits greater efficiency in common operations, most notably matrix multiplication.

mlr3learners extends mlr3 and mlr3proba with interfaces to essential machine learning packages on CRAN. This includes, but is not limited to: (penalized) linear and logistic regression, linear and quadratic discriminant analysis, k-nearest neighbors, naive Bayes, support vector machines, and gradient boosting.

This package defines S4 classes for single-cell genomic data and associated information, such as dimensionality reduction embeddings, nearest-neighbor graphs, and spatially-resolved coordinates. It provides data access methods and R-native hooks to ensure the Seurat object is familiar to other R users.

This package defines S4 classes for single-cell genomic data and associated information, such as dimensionality reduction embeddings, nearest-neighbor graphs, and spatially-resolved coordinates. It provides data access methods and R-native hooks to ensure the Seurat object is familiar to other R users.

Enables gene regulatory network (GRN) analysis on single cell clusters, using the GRN analysis software ANANSE', Xu et al.(2021) <doi:10.1093/nar/gkab598>. Export data from Seurat objects, for GRN analysis by ANANSE implemented in snakemake'. Finally, incorporate results for visualization and interpretation.

This package creates pre- and post- intervention scattergrams based on audiometric data. These scattergrams are formatted for publication in Otology & Neurotology and other otolaryngology journals. For more details, see Gurgel et al (2012) <doi:10.1177/0194599812458401>, Oghalai and Jackler (2016) <doi:10.1177/0194599816638314>.

The goal of equatiomatic is to reduce the pain associated with writing LaTeX formulas from fitted models. The primary function of the package, extract_eq(), takes a fitted model object as its input and returns the corresponding LaTeX code for the model.

Human names are complicated and nonstandard things. Humaniformat, which is based on Anthony Ettinger's humanparser project (https://github.com/ chovy/humanparser) provides functions for parsing human names, making a best- guess attempt to distinguish sub-components such as prefixes, suffixes, middle names and salutations.

Manipulates invertible functions from a finite set to itself. Can transform from word form to cycle form and back. To cite the package in publications please use Hankin (2020) "Introducing the permutations R package", SoftwareX, volume 11 <doi:10.1016/j.softx.2020.100453>.

This package provides beginner friendly framework to analyse population genetic data. Based on adegenet objects it uses knitr to create comprehensive reports on spatial genetic data. For detailed information how to use the package refer to the comprehensive tutorials or visit <http://www.popgenreport.org/>.

Fast multi-trait and multi-trail Genome Wide Association Studies (GWAS) following the method described in Zhou and Stephens. (2014), <doi:10.1038/nmeth.2848>. One of a series of statistical genetic packages for streamlining the analysis of typical plant breeding experiments developed by Biometris.

This package implements adaptive gPCA, as described in: Fukuyama, J. (2017) <arXiv:1702.00501>. The package also includes functionality for applying the method to phyloseq objects so that the method can be easily applied to microbiome data and a shiny app for interactive visualization.

This package provides methods for piecewise smooth regression. A piecewise smooth signal is estimated by applying a bootstrapped test recursively (binary segmentation approach). Each bootstrapped test decides whether the underlying signal is smooth on the currently considered subsegment or contains at least one further change-point.

Identifies genome-related molecular traits with significant evidence of genetic regulation and performs a bootstrap procedure to correct estimated effect sizes for over-estimation present in cis-QTL mapping studies (The "Winner's Curse"), described in Huang QQ *et al.* 2018 <doi: 10.1093/nar/gky780>.

Compute duration curves of daily flow series, both real and modeled, to be compared through indexes of flow duration curves. The package functions include comparative plots and goodness of fit tests. Flow duration curve indexes are based on: Yilmaz et al., (2008) <DOI:10.1029/2007WR006716>.

We consider the non-parametric maximum likelihood estimation of the underlying distribution function, assuming log-concavity, based on mixed-case interval-censored data. The algorithm implemented is base on Chi Wing Chu, Hok Kan Ling and Chaoyu Yuan (2024, <doi:10.48550/arXiv.2411.19878>).

Simple result caching in R based on R.cache. The global environment is not considered when caching results simplifying moving files between multiple instances of R. Relies on more base functions than R.cache (e.g. cached results are saved using saveRDS() and readRDS()).

This package provides tools for Genotype by Environment Interaction (GEI) analysis, using statistical models and visualizations to assess genotype performance across environments. It helps researchers explore interaction effects, stability, and adaptability in multi-environment trials, identifying the best-performing genotypes in different conditions. Which Win Where!