This package provides an R interface to HiGHS, an optimization solver. It is designed for solving mixed-integer optimization problems with quadratic or linear objectives and linear constraints.

Servr provides an HTTP server in R to serve static files, or dynamic documents that can be converted to HTML files (e.g., R Markdown) under a given directory.

mpv is a general-purpose audio and video player. It is a fork of mplayer2 and MPlayer. It shares some features with the former projects while introducing many more.

This package provides a system to build, visualise and evaluate Bayesian belief networks. The methods are described in Stafford et al. (2015) <doi:10.12688/f1000research.5981.1>.

Functions, data and code for Hilbe, J.M. 2011. Negative Binomial Regression, 2nd Edition (Cambridge University Press) and Hilbe, J.M. 2014. Modeling Count Data (Cambridge University Press).

An efficient and convenient set of functions to perform differential network estimation through the use of alternating direction method of multipliers optimization with a variety of loss functions.

This package provides methods and utilities for causal emergence. Used to explore and compute various information theory metrics for networks, such as effective information, effectiveness and causal emergence.

Simultaneous modeling of the quantile and the expected shortfall of a response variable given a set of covariates, see Dimitriadis and Bayer (2019) <doi:10.1214/19-EJS1560>.

Does family-based gene by environment interaction tests, joint gene, gene-environment interaction test, and a test of a set of genes conditional on another set of genes.

An R client for the Federal Reserve Economic Data ('FRED') API <https://research.stlouisfed.org/docs/api/>. Functions to retrieve economic time series and other data from FRED'.

This package provides functions for performing graphical difference testing. Differences are generated between raster images. Comparisons can be performed between different package versions and between different R versions.

Automated analysis and modeling of longitudinal omics data (e.g. breath metabolomics') using generalized spline mixed effect models. Including automated filtering of noise parameters and determination of breakpoints.

This package creates plots of peptides from shotgun proteomics analysis of secretome and lysate samples. These plots contain associated protein features and scores for potential secretion and truncation.

This package provides one function, which is a wrapper around purrr::map() with some extras on top, including parallel computation, progress bars, error handling, and result caching.

Implementation of methods for minimizing ill-conditioned problems. Currently only includes regularized (quasi-)newton optimization (Kanzow and Steck et al. (2023), <doi:10.1007/s12532-023-00238-4>).

Import, process, summarize and visualize raw data from metabolic carts. See Robergs, Dwyer, and Astorino (2010) <doi:10.2165/11319670-000000000-00000> for more details on data processing.

This package contains methods for simulation and for evaluating the pdf, cdf, and quantile functions for symmetric stable, symmetric classical tempered stable, and symmetric power tempered stable distributions.

This package performs hybrid multi-stage factor analytic procedure for controlling acquiescence in restricted solutions (Ferrando & Lorenzo-Seva, 2000 <https://www.uv.es/revispsi/articulos3.00/ferran7.pdf>).

Flexible simulation of time series using time series components, including seasonal, calendar and outlier effects. Main algorithm described in Ollech, D. (2021) <doi:10.1515/jtse-2020-0028>.

Uses thresholded partial least squares algorithm to create a regression or classification model. For more information, see Lee, Bradlow, and Kable <doi:10.1016/j.crmeth.2022.100227>.

This package provides a continuous version of the receiver operating characteristics (ROC) curve to assess both classification and continuity performances of biomarkers, diagnostic tests, or risk prediction models.

This package provides a tool for calculating and drawing "variable trees". Variable trees display information about nested subsets of a data frame. <doi:10.18637/jss.v114.i04>.

Another implementation of general regression neural network in R based on Specht (1991) <DOI:10.1109/72.97934>. It is applicable to the functional approximation or the classification.

RolDE detects longitudinal differential expression between two conditions in noisy high-troughput data. Suitable even for data with a moderate amount of missing values.RolDE is a composite method, consisting of three independent modules with different approaches to detecting longitudinal differential expression. The combination of these diverse modules allows RolDE to robustly detect varying differences in longitudinal trends and expression levels in diverse data types and experimental settings.