Includes bases for litholog generation: graphical functions based on R base graphics, interval management functions and svg importation functions among others. Also include stereographic projection functions, and other functions made to deal with large datasets while keeping options to get into the details of the data. When using for publication please cite Sebastien Wouters, Anne-Christine Da Silva, Frederic Boulvain and Xavier Devleeschouwer, 2021. The R Journal 13:2, 153-178. The palaeomagnetism functions are based on: Tauxe, L., 2010. Essentials of Paleomagnetism. University of California Press. <https://earthref.org/MagIC/books/Tauxe/Essentials/>; Allmendinger, R. W., Cardozo, N. C., and Fisher, D., 2013, Structural Geology Algorithms: Vectors & Tensors: Cambridge, England, Cambridge University Press, 289 pp.; Cardozo, N., and Allmendinger, R. W., 2013, Spherical projections with OSXStereonet: Computers & Geosciences, v. 51, no. 0, p. 193 - 205, <doi: 10.1016/j.cageo.2012.07.021>.

Create Interactive Graph (Network) Visualizations. shinyCyJS can be used in Shiny apps or viewed from Rstudio Viewer. shinyCyJS includes API to build Graph model like node or edge with customized attributes for R. shinyCyJS is built with cytoscape.js and htmlwidgets R package.

Perform the balanced (Scott and Knott, 1974) and unbalanced <doi:10.1590/1984-70332017v17n1a1> Scott & Knott algorithm.

Suite of helper functions for data wrangling and visualization. The only theme for these functions is that they tend towards simple, short, and narrowly-scoped. These functions are built for tasks that often recur but are not large enough in scope to warrant an ecosystem of interdependent functions.

Supports the calculation of meteorological characteristics in evapotranspiration research and reference crop evapotranspiration, and offers three models to simulate crop evapotranspiration and soil water balance in the field, including single crop coefficient and dual crop coefficient, as well as the Shuttleworth-Wallace model. These calculations main refer to Allen et al.(1998, ISBN:92-5-104219-5), Teh (2006, ISBN:1-58-112-998-X), and Liu et al.(2006) <doi:10.1016/j.agwat.2006.01.018>.

Simple SendGrid Email API client for creating and sending emails. For more information, visit the official SendGrid Email API documentation: <https://sendgrid.com/en-us/solutions/email-api>.

This package provides convenience functions to replace hyphen-minuses (ASCII 45) with proper minus signs (Unicode character 2212). The true minus matches the plus symbol in width, line thickness, and height above the baseline. It was designed for mathematics, looks better in presentation, and is understood properly by screen readers.

Estimates sparse regression models (i.e., with few non-zero coefficients) in high-dimensional multi-task learning and transfer learning settings, as proposed by Rauschenberger et al. (2025) <https://orbilu.uni.lu/handle/10993/63425>.

The aim of the package is to provide some basic functions for doing statistics with one dimensional Fuzzy Data (in the form of polygonal fuzzy numbers). In particular, the package contains functions for the basic operations on the class of fuzzy numbers (sum, scalar product, mean, median, Hukuhara difference) as well as for calculating (Bertoluzza) distance and sample variance. Moreover a function to simulate fuzzy random variables and bootstrap tests for the equality of means is included. Version 2.1 fixes some bugs of previous versions.

Reference data sets of species sensitivities to compare the results of fitting species sensitivity distributions using software such as ssdtools and Burrlioz'. It consists of 17 primary data sets from four different Australian and Canadian organizations as well as five datasets from anonymous sources. It also includes a data set of the results of fitting various distributions using different software.

Estimates the parameter of small area in binary data without auxiliary variable using Empirical Bayes technique, mainly from Rao and Molina (2015,ISBN:9781118735787) with book entitled "Small Area Estimation Second Edition". This package provides another option of direct estimation using weight. This package also features alpha and beta parameter estimation on calculating process of small area. Those methods are Newton-Raphson and Moment which based on Wilcox (1979) <doi:10.1177/001316447903900302> and Kleinman (1973) <doi:10.1080/01621459.1973.10481332>.

This package provides a framework that joins topic modeling and sentiment analysis of textual data. The package implements a fast Gibbs sampling estimation of Latent Dirichlet Allocation (Griffiths and Steyvers (2004) <doi:10.1073/pnas.0307752101>) and Joint Sentiment/Topic Model (Lin, He, Everson and Ruger (2012) <doi:10.1109/TKDE.2011.48>). It offers a variety of helpers and visualizations to analyze the result of topic modeling. The framework also allows enriching topic models with dates and externally computed sentiment measures. A flexible aggregation scheme enables the creation of time series of sentiment or topical proportions from the enriched topic models. Moreover, a novel method jointly aggregates topic proportions and sentiment measures to derive time series of topical sentiment.

An outcome-guided algorithm is developed to identify clusters of samples with similar characteristics and survival rate. The algorithm first builds a random forest and then defines distances between samples based on the fitted random forest. Given the distances, we can apply hierarchical clustering algorithms to define clusters. Details about this method is described in <https://github.com/luyouepiusf/SurvivalClusteringTree>.

This package provides a small collection of data on graduate statistics programs from the United States.

This package provides a database-independent JDBC interface.

This package provides a set of functions to build a scoring model from beginning to end, leading the user to follow an efficient and organized development process, reducing significantly the time spent on data exploration, variable selection, feature engineering, binning and model selection among other recurrent tasks. The package also incorporates monotonic and customized binning, scaling capabilities that transforms logistic coefficients into points for a better business understanding and calculates and visualizes classic performance metrics of a classification model.

An introduction to several novel predictive variable selection methods for random forest. They are based on various variable importance methods (i.e., averaged variable importance (AVI), and knowledge informed AVI (i.e., KIAVI, and KIAVI2)) and predictive accuracy in stepwise algorithms. For details of the variable selection methods, please see: Li, J., Siwabessy, J., Huang, Z. and Nichol, S. (2019) <doi:10.3390/geosciences9040180>. Li, J., Alvarez, B., Siwabessy, J., Tran, M., Huang, Z., Przeslawski, R., Radke, L., Howard, F., Nichol, S. (2017). <DOI: 10.13140/RG.2.2.27686.22085>.

An htmlwidget of the human body that allows you to hide/show and assign colors to 79 different body parts. The human widget is an htmlwidget', so it works in Quarto documents, R Markdown documents, or any other HTML medium. It also functions as an input/output widget in a shiny app.

Implementation of the modified skew discrete Laplace (SDL) regression model. The package provides a set of functions for a complete analysis of integer-valued data, where the dependent variable is assumed to follow a modified SDL distribution. This regression model is useful for the analysis of integer-valued data and experimental studies in which paired discrete observations are collected.

This package provides a socket server allows to connect clients to R.

This package provides functions for constructing mathematical models of dynamical systems from measured input-output data.

Collection (syllogi in greek) of real and fictitious data sets for teaching purposes. The datasets were manually entered by the author from the respective references as listed in the individual dataset documentation. The fictions datasets are the creation of the author, that he has found useful for teaching statistics.

Processes amino acid alignments produced by the IPD-IMGT/HLA (Immuno Polymorphism-ImMunoGeneTics/Human Leukocyte Antigen) Database to identify user-defined amino acid residue motifs shared across HLA alleles, HLA alleles, or HLA haplotypes, and calculates frequencies based on HLA allele frequency data. SSHAARP (Searching Shared HLA Amino Acid Residue Prevalence) uses Generic Mapping Tools (GMT) software and the GMT R package to generate global frequency heat maps that illustrate the distribution of each user-defined map around the globe. SSHAARP analyzes the allele frequency data described by Solberg et al. (2008) <doi:10.1016/j.humimm.2008.05.001>, a global set of 497 population samples from 185 published datasets, representing 66,800 individuals total. Users may also specify their own datasets, but file conventions must follow the prebundled Solberg dataset, or the mock haplotype dataset.

The single cell mapper (scMappR) R package contains a suite of bioinformatic tools that provide experimentally relevant cell-type specific information to a list of differentially expressed genes (DEG). The function "scMappR_and_pathway_analysis" reranks DEGs to generate cell-type specificity scores called cell-weighted fold-changes. Users input a list of DEGs, normalized counts, and a signature matrix into this function. scMappR then re-weights bulk DEGs by cell-type specific expression from the signature matrix, cell-type proportions from RNA-seq deconvolution and the ratio of cell-type proportions between the two conditions to account for changes in cell-type proportion. With cwFold-changes calculated, scMappR uses two approaches to utilize cwFold-changes to complete cell-type specific pathway analysis. The "process_dgTMatrix_lists" function in the scMappR package contains an automated scRNA-seq processing pipeline where users input scRNA-seq count data, which is made compatible for scMappR and other R packages that analyze scRNA-seq data. We further used this to store hundreds up regularly updating signature matrices. The functions "tissue_by_celltype_enrichment", "tissue_scMappR_internal", and "tissue_scMappR_custom" combine these consistently processed scRNAseq count data with gene-set enrichment tools to allow for cell-type marker enrichment of a generic gene list (e.g. GWAS hits). Reference: Sokolowski,D.J., Faykoo-Martinez,M., Erdman,L., Hou,H., Chan,C., Zhu,H., Holmes,M.M., Goldenberg,A. and Wilson,M.D. (2021) Single-cell mapper (scMappR): using scRNA-seq to infer cell-type specificities of differentially expressed genes. NAR Genomics and Bioinformatics. 3(1). Iqab011. <doi:10.1093/nargab/lqab011>.