For a single variable, the IVY Plot stacks tied values in the form of leaflets. Five leaflets join to form a leaf. Leaves are stacked vertically. At most twenty leaves are shown; For high frequency, each leaflet may represent more than one observation with multiplicity declared in the subtitle.

R is great for installing software. Through the installr package you can automate the updating of R (on Windows, using updateR()) and install new software. Software installation is initiated through a GUI (just run installr()), or through functions such as: install.Rtools(), install.pandoc(), install.git(), and many more. The updateR() command performs the following: finding the latest R version, downloading it, running the installer, deleting the installation file, copy and updating old packages to the new R installation.

This package provides a bunch of functions to deal with circular data under order restrictions.

Includes a collection of shiny applications to demonstrate or to explore fundamental item response theory (IRT) concepts such as estimation, scoring, and multidimensional IRT models.

This package provides a set of functions to run simple and composite box-models to describe the dynamic or static distribution of stable isotopes in open or closed systems. The package also allows the sweeping of many parameters in both static and dynamic conditions. The mathematical models used in this package are derived from Albarede, 1995, Introduction to Geochemical Modelling, Cambridge University Press, Cambridge <doi:10.1017/CBO9780511622960>.

Coefficients of Interrater Reliability and Agreement for quantitative, ordinal and nominal data: ICC, Finn-Coefficient, Robinson's A, Kendall's W, Cohen's Kappa, ...

Import and export data from the most common statistical formats by using R functions that guarantee the least loss of the data information, giving special attention to the date variables and the labelled ones.

This package provides tools for probabilistic taxon assignment with informatic sequence classification trees. See Wilkinson et al (2018) <doi:10.7287/peerj.preprints.26812v1>.

Integrated toolbox supporting common file formats used for intracranial Electroencephalography (iEEG) and deep-brain stimulation (DBS) study.

Reproducible, programmatic retrieval of datasets from the Inter-university Consortium for Political and Social Research archive.

Flexibly implements Integral Projection Models using a mathematical(ish) syntax. This package will not help with the vital rate modeling process, but will help convert those regression models into an IPM. ipmr handles density dependence and environmental stochasticity, with a couple of options for implementing the latter. In addition, provides functions to avoid unintentional eviction of individuals from models. Additionally, provides model diagnostic tools, plotting functionality, stochastic/deterministic simulations, and analysis tools. Integral projection models are described in depth by Easterling et al. (2000) <doi:10.1890/0012-9658(2000)081[0694:SSSAAN]2.0.CO;2>, Merow et al. (2013) <doi:10.1111/2041-210X.12146>, Rees et al. (2014) <doi:10.1111/1365-2656.12178>, and Metcalf et al. (2015) <doi:10.1111/2041-210X.12405>. Williams et al. (2012) <doi:10.1890/11-2147.1> discuss the problem of unintentional eviction.

Estimation of joint models for multivariate longitudinal markers (with various distributions available) and survival outcomes (possibly accounting for competing risks) with Integrated Nested Laplace Approximations (INLA). The flexible and user friendly function joint() facilitates the use of the fast and reliable inference technique implemented in the INLA package for joint modeling. More details are given in the help page of the joint() function (accessible via ?joint in the R console) and the vignette associated to the joint() function (accessible via vignette("INLAjoint") in the R console).

Pre-processing and basic analytical tasks for working with Eurostat's symmetric inputâ output tables, and basic inputâ output economics calculations. Part of rOpenGov <https://ropengov.github.io/> for open source open government initiatives.

An implementation of the Otsu's Image Segmentation Method described in the paper: "A C++ Implementation of Otsu's Image Segmentation Method". The algorithm is explained at <doi:10.5201/ipol.2016.158>.

This package implements multiple variants of the Information Bottleneck ('IB') method for clustering datasets containing continuous, categorical (nominal/ordinal) and mixed-type variables. The package provides deterministic, agglomerative, generalized, and standard IB clustering algorithms that preserve relevant information while forming interpretable clusters. The Deterministic Information Bottleneck is described in Costa et al. (2024) <doi:10.48550/arXiv.2407.03389>. The standard IB method originates from Tishby et al. (2000) <doi:10.48550/arXiv.physics/0004057>, the agglomerative variant from Slonim and Tishby (1999) <https://papers.nips.cc/paper/1651-agglomerative-information-bottleneck>, and the generalized IB from Strouse and Schwab (2017) <doi:10.1162/NECO_a_00961>.

This package provides tools to extract information from the Intergovernmental Organizations ('IGO') Database , version 3, provided by the Correlates of War Project <https://correlatesofwar.org/>. See also Pevehouse, J. C. et al. (2020). Version 3 includes information from 1815 to 2014.

Distributional regression under stochastic order restrictions for numeric and binary response variables and partially ordered covariates. See Henzi, Ziegel, Gneiting (2020) <arXiv:1909.03725>.

Collection of functions for IO Psychologists.

An implementation of generalized linear models (GLMs) for studying relationships among attributes in connected populations, where responses of connected units can be dependent, as introduced by Fritz et al. (2025) <doi:10.1080/01621459.2025.2565851>. igml extends GLMs for independent responses to dependent responses and can be used for studying spillover in connected populations and other network-mediated phenomena.

An implementation of the initial guided analytics for parameter testing and controlband extraction framework. Functions are available for continuous and categorical target variables as well as for generating standardized reports of the conducted analysis. See <https://github.com/stefan-stein/igate> for more information on the technology.

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>.

Plots the conditional coefficients ("marginal effects") of variables included in multiplicative interaction terms.

This package provides functions to clean and process international trade data into an international trade network (ITN) are provided. It then provides a set a functions to undertake analysis and plots of the ITN (extract the backbone, centrality, blockmodels, clustering). Examining the key players in the ITN and regional trade patterns.

Calculates various chance-corrected agreement coefficients (CAC) among 2 or more raters are provided. Among the CAC coefficients covered are Cohen's kappa, Conger's kappa, Fleiss kappa, Brennan-Prediger coefficient, Gwet's AC1/AC2 coefficients, and Krippendorff's alpha. Multiple sets of weights are proposed for computing weighted analyses. All of these statistical procedures are described in details in Gwet, K.L. (2014,ISBN:978-0970806284): "Handbook of Inter-Rater Reliability," 4th edition, Advanced Analytics, LLC.