This package provides an R-based solution for symbolic differentiation. It admits user-defined functions as well as function substitution in arguments of functions to be differentiated. Some symbolic simplification is part of the work.

This package performs approximate bayesian computation (ABC) model choice and parameter inference via random forests. This machine learning tool named random forests (RF) can conduct selection among the highly complex models covered by ABC algorithms.

Makes it incredibly easy to build interactive web applications with R. Automatic "reactive" binding between inputs and outputs and extensive prebuilt widgets make it possible to build beautiful, responsive, and powerful applications with minimal effort.

This package provides a set of functions to run R code in an environment in which global state has been temporarily modified. Many of these functions were originally a part of the r-devtools package.

This package tests the goodness of fit of a distribution of offspring to the Normal, Poisson, and Gamma distribution and estimates the proportional paternity of the second male (P2) based on the best fit distribution.

RNNoise is a noise suppression library based on a recurrent neural network. The algorithm is described in Jean-Marc Valin's paper A Hybrid DSP/Deep Learning Approach to Real-Time Full-Band Speech Enhancement.

This package performs the colocalisation tests described in Giambartolomei et al (2013) <doi:10.1371/journal.pgen.1004383>, Wallace (2020) <doi:10.1371/journal.pgen.1008720>, Wallace (2021) <doi:10.1371/journal.pgen.1009440>.

This package implements the convex clustering through majorization-minimization (CCMM) algorithm described in Touw, Groenen, and Terada (2022) <doi:10.48550/arXiv.2211.01877> to perform minimization of the convex clustering loss function.

Manipulates date ('Date'), date time ('POSIXct') and time ('hms') vectors. Date/times are considered discrete and are floored whenever encountered. Times are wrapped and time zones are maintained unless explicitly altered by the user.

Enhances decision tree visualization by incorporating Generalized Association Plots (GAP) through matrix-based visualizations including confusion matrix maps, decision tree matrix maps, and predicted class membership maps based on supervised correlation and distance metrics.

This package provides functions for (1) ranking, selecting, and prioritising genes, proteins, and metabolites from high dimensional biology experiments, (2) multivariate hit calling in high content screens, and (3) combining data from diverse sources.

The Discrete Transmuted Generalized Inverse Weibull (DTGIW) distribution is a new distribution for count data analysis. The DTGIW is discrete distribution based on Atchanut and Sirinapa (2021). <DOI: 10.14456/sjst-psu.2021.149>.

Bayesian nonlinear regression under a range of likelihood models using generalized Bayesian adaptive smoothing splines. Robust regression with Student's t likelihoods, quantile regression, and related latent-scale models are included as special cases.

Make it easy to create simplified trial summary (TS) domain based on FDA FDA guide <https://github.com/TuCai/phuse/blob/master/inst/examples/07_genTS/www/Simplified_TS_Creation_Guide_v2.pdf>.

Functional denoising and functional ANOVA through wavelet-domain Markov groves. Fore more details see: Ma L. and Soriano J. (2018) Efficient functional ANOVA through wavelet-domain Markov groves. <arXiv:1602.03990v2 [stat.ME]>.

Analyze small-sample clustered or longitudinal data using modified generalized estimating equations with bias-adjusted covariance estimator. The package provides any combination of three modified generalized estimating equations and 11 bias-adjusted covariance estimators.

This package provides a network-based gene weighting algorithm for pathway enrichment analysis, using either RNA-seq or microarray data. Zhaoyuan Fang, Weidong Tian and Hongbin Ji (2012) <doi:10.1038/cr.2011.149>.

An offline suite of tools to clean, aggregate, and harmonise data from the Malawi Integrated Household Survey ('IHS'). Provides crop-specific unit conversions, stratified winsorization, and automatic cross-round harmonisation for complex survey designs.

This package provides a personalized dynamic latent factor model (Zhang et al. (2024) <doi:10.1093/biomet/asae015>) for irregular multi-resolution time series data, to interpolate unsampled measurements from low-resolution time series.

This package provides a macro language for R programs, which provides a macro facility similar to SAS®'. This package contains basic macro capabilities like defining macro variables, executing conditional logic, and defining macro functions.

This package contains functions for converting existing HTML/JavaScript source into equivalent shiny functions. Bootstraps the process of making new shiny functions by allowing us to turn HTML snippets directly into R functions.

This package provides a toolkit for medical records data analysis. The naryn package implements an efficient data structure for storing medical records, and provides a set of functions for data extraction, manipulation and analysis.

Wrapper around the Open Source Routing Machine (OSRM) API <http://project-osrm.org/>. osrmr works with API versions 4 and 5 and can handle servers that run locally as well as the OSRM webserver.

Spatial estimation of a prevalence surface or a relative risks surface, using data from a Demographic and Health Survey (DHS) or an analog survey, see Larmarange et al. (2011) <doi:10.4000/cybergeo.24606>.