Build regular expressions piece by piece using human readable code. This package contains number-related functionality, and is primarily intended to be used by package developers.

This package implements a high performance C++ parser for ActiGraph GT3X'/'GT3X+ data format (with extension .gt3x') for accelerometer samples. Activity samples can be easily read into a matrix or data.frame. This allows for storing the raw accelerometer samples in the original binary format to reserve space.

This package provides a series of functions that allow users to access the LinkedIn API to get information about connections, search for people and jobs, share updates with their network, and create group discussions. For more information about using the API please visit <https://developer.linkedin.com/>.

Gene annotation of rice (Oryza Sativa L.spp.japonica). The package is based on the annotation file from the website <http://plants.ensembl.org/Oryza_sativa/Info/Index>. Input gene's name then return some information, including the from position, the end position, the position type and the chromosome number.

Some heavily used base R functions are reconstructed to also be compliant to data.table objects. Also, some general helper functions that could be of interest for working with data.table objects are included.

Useful tools for determining whether two samples are from the same distribution. Utilizes a robust method to address the problematic structure of the similarity graph constructed from high-dimensional data. The method is provided in Yichuan Bai and Lynna Chu (2023) <arXiv:2307.12325>.

The rkafkajars package collects all the external jars required for the rkafka package.

This package provides functions from the book "Reinsurance: Actuarial and Statistical Aspects" (2017) by Hansjoerg Albrecher, Jan Beirlant and Jef Teugels <https://www.wiley.com/en-us/Reinsurance%3A+Actuarial+and+Statistical+Aspects-p-9780470772683>.

Simplifies integration with Amazon Cognito (<https://aws.amazon.com/cognito/>) for R developers, enabling easy management of user authentication, registration, and password flows.

Routines that allow the user to run a large number of goodness-of-fit tests. It allows for data to be continuous or discrete. It includes routines to estimate the power of the tests and display them as a power graph. The routine run.studies allows a user to quickly study the power of a new method and how it compares to some of the standard ones.

This package provides functions for cleaning and summarising water quality data for use in National Pollutant Discharge Elimination Service (NPDES) permit reasonable potential analyses and water quality-based effluent limitation calculations. Procedures are based on those contained in the "Technical Support Document for Water Quality-based Toxics Control", United States Environmental Protection Agency (1991).

Updates values within csv format data files using a custom, User-built csv format lookup file. Based on data.table package.

This package implements popular methods for matching in time-varying observational studies. Matching is difficult in this scenario because participants can be treated at different times which may have an influence on the outcomes. The core methods include: "Balanced Risk Set Matching" from Li, Propert, and Rosenbaum (2011) <doi:10.1198/016214501753208573> and "Propensity Score Matching with Time-Dependent Covariates" from Lu (2005) <doi:10.1111/j.1541-0420.2005.00356.x>. Some functions use the Gurobi optimization back-end to improve the optimization problem speed; the gurobi R package and associated software can be downloaded from <https://www.gurobi.com> after obtaining a license.

The R commander plug-in for robust principal component analysis. The Graphical User Interface for Principal Component Analysis (PCA) with Hubert Algorithm method.

Tu & Zhou (1999) <doi:10.1002/(SICI)1097-0258(19991030)18:20%3C2749::AID-SIM195%3E3.0.CO;2-C> showed that comparing the means of populations whose data-generating distributions are non-negative with excess zero observations is a problem of great importance in the analysis of medical cost data. In the same study, Tu & Zhou discuss that it can be difficult to control type-I error rates of general-purpose statistical tests for comparing the means of these particular data sets. This package allows users to perform a modified bootstrap-based t-test that aims to better control type-I error rates in these situations.

Determination of rainfall-runoff erosivity factor.

Visualize networks using the javascript library roughjs'. This allows to draw sketchy, hand-drawn-like networks.

R6 class interface for handling relational database connections using DBI package as backend. The class allows handling of connections to e.g. PostgreSQL, MariaDB and SQLite. The purpose is having an intuitive object allowing straightforward handling of SQL databases.

This package provides a supportive collection of functions for gathering and plotting treatment ranking metrics after network meta-analysis.

The visualization tool offers a nuanced understanding of regression dynamics, going beyond traditional per-unit interpretation of continuous variables versus categorical ones. It highlights the impact of unit changes as well as larger shifts like interquartile changes, acknowledging the distribution of empirical data. Furthermore, it generates visualizations depicting alterations in Odds Ratios for predictors across minimum, first quartile, median, third quartile, and maximum values, aiding in comprehending predictor-outcome interplay within empirical data distributions, particularly in logistic regression frameworks.

This package implements diversification analyses using the phylogenetic birth-death-shift model. It leverages belief propagation techniques to calculate branch-specific diversification rates, see Kopperud & Hoehna (2025) <doi:10.1093/sysbio/syaf041>.

Utility functions for interacting with the COMPADRE and COMADRE databases of matrix population models. Described in Jones et al. (2021) <doi:10.1101/2021.04.26.441330>.

Compute yield-stability index based on Bayesian methodology, which is useful for analyze multi-environment trials in plant breeding programs. References: Cotes Torres JM, Gonzalez Jaimes EP, and Cotes Torres A (2016) <https://revistas.unimilitar.edu.co/index.php/rfcb/article/view/2037> Seleccion de Genotipos con Alta Respuesta y Estabilidad Fenotipica en Pruebas Regionales: Recuperando el Concepto Biologico.

Solves the individual bioenergetic balance for different aquaculture sea fish (Sea Bream and Sea Bass; Brigolin et al., 2014 <doi:10.3354/aei00093>) and shellfish (Mussel and Clam; Brigolin et al., 2009 <doi:10.1016/j.ecss.2009.01.029>; Solidoro et al., 2000 <doi:10.3354/meps199137>). Allows for spatialized model runs and population simulations.