This package provides functions to analyse missing value mechanisms and to impute data sets in the context of bottom-up MS-based proteomics.

Generates image data for fractals (Julia and Mandelbrot sets) on the complex plane in the given region and resolution. Benoit B Mandelbrot (1982).

Implementation of the drift-diffusion mixed model for category learning as described in Paulon et al. (2021) <doi:10.1080/01621459.2020.1801448>.

This package provides real & simulated datasets containing time-series traffic observations and additional information pertaining to Loop 1 "Mopac" located in Austin, Texas.

Perform correlation and linear regression test among the numeric fields in a data.frame automatically and make plots using pairs or lattice::parallelplot.

Implementation of Multidimensional Top Scoring method for creativity assessment proposed in Boris Forthmann, Maciej Karwowski, Roger E. Beaty (2023) <doi:10.1037/aca0000571>.

Conduct sensitivity analysis of omitted variable bias in linear econometric models using the methodology presented in Basu (2025) <doi:10.2139/ssrn.4704246>.

Build SVG components using element-based functions. With an svg object, we can modify its graphical elements with a suite of transform functions.

This package provides tools for collecting municipal-level data <http://www.transparencia.gov.br/swagger-ui.html> from several Brazilian governmental social programs.

We provide several algorithms to compute the genotype ancestry scores (such as eigenvector projections) in the case where highly correlated individuals are involved.

This package provides a method for estimating log-normalizing constants (or free energies) and expectations from multiple distributions (such as multiple generalized ensembles).

This package provides a clean syntax for vectorising the use of Non-Standard Evaluation (NSE), for example in ggplot2', dplyr', or data.table'.

Converts weekly data to monthly data. Users can use three types of week formats: ISO week, epidemiology week (epi week) and calendar date.

An alternative canonical correlation/redundancy analysis function, with associated print, plot, and summary methods. A method for generating helio plots is also included.

Utilities for simplifying common statistical operations including probability density functions, cumulative distribution functions, Kolmogorov-Smirnov tests, principal component analysis plots, and prediction plots.

Represents high-dimensional data as tables of features, samples and measurements, and a design list for tracking the meaning of individual variables. Using this format, filtering, normalization, and other transformations of a dataset can be carried out in a flexible manner. romic takes advantage of these transformations to create interactive shiny apps for exploratory data analysis such as an interactive heatmap.

Interface to easily access data via the United States Department of Agriculture (USDA)'s Agricultural Resource Management Survey (ARMS) Data API <https://www.ers.usda.gov/developer/data-apis/arms-data-api/>. The downloaded data can be saved for later off-line use. Also provide relevant information and metadata for each of the input variables needed for sending the data inquery.

An AI copilot for R users in RStudio and Posit workflows with active-editor, workspace, object, console, plot, and git-aware context. Provides statistical helpers for interpreting lm() and glm() models, stages code and file actions before execution, drafts reproducible Quarto content, and connects to official provider APIs or CLIs for OpenAI', GitHub Copilot', Gemini', and Anthropic'.

Calculates tide heights based on tide station harmonics. It includes the harmonics data for 637 US stations. The harmonics data was converted from <https://github.com/poissonconsulting/rtide/blob/main/data-raw/harmonics-dwf-20151227-free.tar.bz2>, NOAA web site data processed by David Flater for XTide'. The code to calculate tide heights from the harmonics is based on XTide'.

Routines to select and visualize the maxima for a given strict partial order. This especially includes the computation of the Pareto frontier, also known as (Top-k) Skyline operator (see Börzsönyi, et al. (2001) <doi:10.1109/ICDE.2001.914855>), and some generalizations known as database preferences (see Kieà ling (2002) <doi:10.1016/B978-155860869-6/50035-4>).

MCFS-ID (Monte Carlo Feature Selection and Interdependency Discovery) is a Monte Carlo method-based tool for feature selection. It also allows for the discovery of interdependencies between the relevant features. MCFS-ID is particularly suitable for the analysis of high-dimensional, small n large p transactional and biological data. M. Draminski, J. Koronacki (2018) <doi:10.18637/jss.v085.i12>.

The TRIM model is widely used for estimating growth and decline of animal populations based on (possibly sparsely available) count data. The current package is a reimplementation of the original TRIM software developed at Statistics Netherlands by Jeroen Pannekoek. See <https://www.cbs.nl/en-gb/society/nature-and-environment/indices-and-trends%2d%2dtrim%2d%2d> for more information about TRIM.

Fit Class Cover Catch Digraph Classification models that can be used in machine learning. Pure and proper and random walk approaches are available. Methods are explained in Priebe et al. (2001) <doi:10.1016/S0167-7152(01)00129-8>, Priebe et al. (2003) <doi:10.1007/s00357-003-0003-7>, and Manukyan and Ceyhan (2016) <doi:10.48550/arXiv.1904.04564>.

The package includes quality control metrics, a selection of normalization methods and novel methods to identify differentially methylated regions and to highlight copy number alterations.