Allows the simulation of the recruitment and both the event and treatment phase of a clinical trial. Based on these simulations, the timing of interim analyses can be assessed.

Launches a shiny based application for Nuclear Magnetic Resonance (NMR)data importation and Statistical TOtal Correlation SpectroscopY (STOCSY) analyses in a full interactive approach. The theoretical background and applications of STOCSY method could be found at Cloarec, O., Dumas, M. E., Craig, A., Barton, R. H., Trygg, J., Hudson, J., Blancher, C., Gauguier, D., Lindon, J. C., Holmes, E. & Nicholson, J. (2005) <doi:10.1021/ac048630x>.

Enable user to find the IP addresses which are used as VPN anonymizer, open proxies, web proxies and Tor exits. The package lookup the proxy IP address from IP2Proxy BIN Data file. You may visit <https://lite.ip2location.com> for free database download.

Spatial interpolation toolkit designed for environmental and geospatial applications. It includes a range of methods, from traditional techniques to advanced machine learning approaches, ensuring accurate and efficient estimation of values in unobserved locations.

The IntCal20 radiocarbon calibration curves (Reimer et al. 2020 <doi:10.1017/RDC.2020.68>) are provided here in a single data package, together with previous IntCal curves (IntCal13, IntCal09, IntCal04, IntCal98) and postbomb curves. Also provided are functions to copy the curves into memory, and to plot the curves and their underlying data, as well as functions to calibrate radiocarbon dates.

Graphical visualization tools for analyzing the data produced by irace'. The iraceplot package enables users to analyze the performance and the parameter space data sampled by the configuration during the search process. It provides a set of functions that generate different plots to visualize the configurations sampled during the execution of irace and their performance. The functions just require the log file generated by irace and, in some cases, they can be used with user-provided data.

It provides in-place operators for R that are equivalent to +=', -=', *=', /= in C++. Those can be applied on integer|double vectors|matrices. You have also access to sweep operations (in-place).

Package provides tools for modular Bayesian model calibration. these tools allow for posterior exploration with sampling methods including tempering and adaptive Markov Chain Monte Carlo (MCMC). Allows for pooled calibration or hierarchal calibration of parameters. For more information see Francom et al., 2025 <DOI:10.1137/24M1644092>.

This package provides advanced functions for image processing based on the package imager'.

An implementation of the MaxLFQ algorithm by Cox et al. (2014) <doi:10.1074/mcp.M113.031591> in a comprehensive pipeline for processing proteomics data in data-independent acquisition mode (Pham et al. 2020 <doi:10.1093/bioinformatics/btz961>; Pham et al. 2026 <doi:10.1021/acs.jproteome.5c01038>). It offers additional options for protein quantification using the N most intense fragment ions, using all fragment ions, the median polish algorithm by Tukey (1977, ISBN:0201076160), and a robust linear model. In general, the tool can be used to integrate multiple proportional observations into a single quantitative value.

This package provides classes and functions for working with IP (Internet Protocol) addresses and networks, inspired by the Python ipaddress module. Offers full support for both IPv4 and IPv6 (Internet Protocol versions 4 and 6) address spaces. It is specifically designed to work well with the tidyverse'.

This package provides ability to create color palettes from image files. It offers control over the type of color palette to derive from an image (qualitative, sequential or divergent) and other palette properties. Quantiles of an image color distribution can be trimmed. Near-black or near-white colors can be trimmed in RGB color space independent of trimming brightness or saturation distributions in HSV color space. Creating sequential palettes also offers control over the order of HSV color dimensions to sort by. This package differs from other related packages like RImagePalette in approaches to quantizing and extracting colors in images to assemble color palettes and the level of user control over palettes construction.

This package provides a collection of Irucka Embry's miscellaneous USGS functions (processing .exp and .psf files, statistical error functions, "+" dyadic operator for use with NA, creating ADAPS and QW spreadsheet files, calculating saturated enthalpy). Irucka created these functions while a Cherokee Nation Technology Solutions (CNTS) United States Geological Survey (USGS) Contractor and/or USGS employee.

Estimates the density of a spatially distributed animal population sampled with an array of passive detectors, such as traps. Models incorporating distance-dependent detection are fitted by simulation and inverse prediction as proposed by Efford (2004) <doi:10.1111/j.0030-1299.2004.13043.x>.

Functionality required to efficiently use R with IBM(R) Db2(R) Warehouse offerings (formerly IBM dashDB(R)) and IBM Db2 for z/OS(R) in conjunction with IBM Db2 Analytics Accelerator for z/OS. Many basic and complex R operations are pushed down into the database, which removes the main memory boundary of R and allows to make full use of parallel processing in the underlying database. For executing R-functions in a multi-node environment in parallel the idaTApply() function requires the SparkR package (<https://spark.apache.org/docs/latest/sparkr.html>). The optional ggplot2 package is needed for the plot.idaLm() function only.

This package provides actuarial tools and building blocks for analysing, modelling, refining, and validating insurance rating models. Designed to support common GLM-based pricing tasks and the translation of statistical model output into practical tariff structures. The package supports the construction of insurance tariff classes using a data-driven approach, based on the methodology of Antonio and Valdez (2012) <doi:10.1007/s10182-011-0152-7>.

This package contains techniques for mining large and high-dimensional data sets by using the concept of Intrinsic Dimension (ID). Here the ID is not necessarily an integer. It is extended to fractal dimensions. And the Morisita estimator is used for the ID estimation, but other tools are included as well.

Implementation of some of the formulations for the thermodynamic and transport properties released by the International Association for the Properties of Water and Steam (IAPWS). More specifically, the releases R1-76(2014), R5-85(1994), R6-95(2018), R7-97(2012), R8-97, R9-97, R10-06(2009), R11-24, R12-08, R15-11, R16-17(2018), R17-20 and R18-21 at <https://iapws.org>.

Implementation of Tyler, Critchley, Duembgen and Oja's (JRSS B, 2009, <doi:10.1111/j.1467-9868.2009.00706.x>) and Oja, Sirkia and Eriksson's (AJS, 2006, <https://www.ajs.or.at/index.php/ajs/article/view/vol35,%20no2%263%20-%207>) method of two different scatter matrices to obtain an invariant coordinate system or independent components, depending on the underlying assumptions.

Used for analyzing immune responses and predicting vaccine efficacy using machine learning and advanced data processing techniques. Immunaut integrates both unsupervised and supervised learning methods, managing outliers and capturing immune response variability. It performs multiple rounds of predictive model testing to identify robust immunogenicity signatures that can predict vaccine responsiveness. The platform is designed to handle high-dimensional immune data, enabling researchers to uncover immune predictors and refine personalized vaccination strategies across diverse populations.

This package provides functions to compute and plot Krippendorff's inter-coder reliability coefficient alpha and bootstrapped uncertainty estimates (Krippendorff 2004, ISBN:0761915443). The bootstrap routines are set up to make use of parallel threads where supported.

This package implements continuous-time hidden Markov models (HMMs) to infer identity-by-descent (IBD) segments shared by two individuals from their single-nucleotide polymorphism (SNP) genotypes. Provides posterior probabilities at each marker (forward-backward algorithm), prediction of IBD segments (Viterbi algorithm), and functions for visualising results. Supports both autosomal data and X-chromosomal data.

Characterisation and calibration of single or multiple Ion Selective Electrodes (ISEs); activity estimation of experimental samples. Implements methods described in: Dillingham, P.W., Radu, T., Diamond, D., Radu, A. and McGraw, C.M. (2012) <doi:10.1002/elan.201100510>, Dillingham, P.W., Alsaedi, B.S.O. and McGraw, C.M. (2017) <doi:10.1109/ICSENS.2017.8233898>, Dillingham, P.W., Alsaedi, B.S.O., Radu, A., and McGraw, C.M. (2019) <doi:10.3390/s19204544>, and Dillingham, P.W., Alsaedi, B.S.O., Granados-Focil, S., Radu, A., and McGraw, C.M. (2020) <doi:10.1021/acssensors.9b02133>.

Offers a pipe-friendly alternative to the dplyr functions case_when() and if_else(), as well as a number of user-friendly simplifications for common use cases. These functions accept a vector as an optional first argument, allowing conditional statements to be built using the magrittr dot operator. The functions also coerce all outputs to the same type, meaning you no longer have to worry about using specific typed variants of NA or explicitly declaring integer outputs, and evaluate outputs somewhat lazily, so you don't waste time on long operations that won't be used.