Detection of ligand-protein interactions from 2D thermal profiles (DLPTP), Performs an FDR-controlled analysis of 2D-TPP experiments by functional analysis of dose-response curves across temperatures.

This package is devoted to analyzing MeRIP-seq data. Current functionalities include 1. detect transcriptome wide m6A methylation regions 2. detect transcriptome wide differential m6A methylation regions.

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).

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>.

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'.

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.

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.

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>).

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.

R's implementation of the JavaScript library path-to-regexp', it aims to provide R web frameworks features such as parameter handling among other URL path utilities.

This package provides routines to check identifiability of linear structural equation models and factor analysis models. The routines are based on the graphical representation of structural equation models.

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.

Miscellaneous supplementary functions designed to follow idiomatic R conventions. Some functions are simple wrappers that reduce repetitive code, while others address common tasks or extend existing R functions.

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>).

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.

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>.

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>.

This package provides easy access to a curated selection of pre-processed data sets relevant to the COVID-19 outbreak in the UK for teaching and demonstration purposes.

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.