Compute time-dependent Incident/dynamic accuracy measures (ROC curve, AUC, integrated AUC )from censored survival data under proportional or non-proportional hazard assumption of Heagerty & Zheng (Biometrics, Vol 61 No 1, 2005, PP 92-105).

Generates plots from a database connection and a SGL statement. SGL is a graphics language designed to look and feel like SQL'. It is especially useful for those familiar with SQL who want to specify plots in a similar manner. The SGL language is described in Chapman (2025) <doi:10.48550/arXiv.2505.14690>.

The ability to plot raster graphics in PDF files can be useful when one needs multi-page documents, but the plots contain so many individual elements that (the usual) use of vector graphics results in inconveniently large file sizes. Internally, the package plots each individual page as a PNG, and then combines them in one PDF file.

Sends texts to the <https://www.receptiviti.com> API to be scored, and facilitates the creation of custom norms and local results databases.

An extension package for sparklyr that provides an R interface to H2O Sparkling Water machine learning library (see <https://github.com/h2oai/sparkling-water> for more information).

This package provides a collection of shiny applications for the R package Luminescence'. These mainly, but not exclusively, include applications for plotting chronometric data from e.g. luminescence or radiocarbon dating. It further provides access to bootstraps tooltip and popover functionality and contains the jscolor.js library with a custom shiny output binding.

Response surface designs with neighbour effects are suitable for experimental situations where it is expected that the treatment combination administered to one experimental unit may affect the response on neighboring units as well as the response on the unit to which it is applied (Dalal et al.,2025 <doi: 10.57805/revstat.v23i2.513>). Integrating these effects in the response surface model improves the experiment's precision Verma A., Jaggi S., Varghese, E.,Varghese, C.,Bhowmik, A., Datta, A. and Hemavathi M. (2021)<doi: 10.1080/03610918.2021.1890123>). This package includes sym(), asym1(), asym2(), asym3() and asym4() functions that generates response surface designs which are rotatable under a polynomial model of a given order without interaction term incorporating neighbour effects.

This package provides clean, tidy access to statistical data published by the European Central Bank ('ECB') via the ECB Data Portal API <https://data.ecb.europa.eu>. Covers policy interest rates, EURIBOR', euro exchange rates, harmonised consumer price inflation ('HICP'), euro area yield curves, the euro short-term rate ('ESTR'), monetary aggregates (M1, M2, M3), mortgage and lending rates, GDP, unemployment, and government debt-to-GDP. Each dataset has a dedicated function that abstracts away the underlying SDMX key structure, so users do not need to know series codes. A generic fetcher is also provided for direct access to any of the ECB 100-plus dataflows. Data is downloaded on first use and cached locally for subsequent calls.

Provide simple mechanism to repeatedly evaluate an expression until either it succeeds or timeout exceeded. It is useful in situations that random failures could happen.

The Rcpp package contains a C++ library that facilitates the integration of R and C++ in various ways via a rich API. This API was preceded by an earlier version which has been deprecated since 2010 (but is still supported to provide backwards compatibility in the package RcppClassic'). This package RcppClassicExamples provides usage examples for the older, deprecated API. There is also a corresponding package RcppExamples with examples for the newer, current API which we strongly recommend as the basis for all new development.

This package provides an R6 class and several utility methods to facilitate the implementation of models based on ordinary differential equations. The heart of the package is a code generator that creates compiled Fortran (or R') code which can be passed to a numerical solver. There is direct support for solvers contained in packages deSolve and rootSolve'.

This package provides a programmatic interface to the Request Tracker (RT) HTTP API <https://rt-wiki.bestpractical.com/wiki/REST>. RT is a popular ticket tracking system.

Packed bar charts are a variation of treemaps for visualizing skewed data. The concept was introduced by Xan Gregg at JMP'.

This package contains various tools to estimate, analyze, and visualize Response Item Networks. ResIN dummy-codes ordered and qualitative response choices from (survey) data, calculates pairwise associations and maps the location of each item response as a node in a force-directed network. Please refer to <https://www.resinmethod.net/> for more details.

Creation, manipulation, simulation of linear Gaussian Bayesian networks from text files and more...

R wrapper of the libmf library <https://www.csie.ntu.edu.tw/~cjlin/libmf/> for recommender system using matrix factorization. It is typically used to approximate an incomplete matrix using the product of two matrices in a latent space. Other common names for this task include "collaborative filtering", "matrix completion", "matrix recovery", etc. High performance multi-core parallel computing is supported in this package.

Recursive lists in the form of R objects, JSON', and XML', for use in teaching and examples. Examples include color palettes, Game of Thrones characters, GitHub users and repositories, music collections, and entities from the Star Wars universe. Data from the gapminder package is also included, as a simple data frame and in nested and split forms.

Discretize AR(1) process following Tauchen (1986) <http://www.sciencedirect.com/science/article/pii/0165176586901680>. A discrete Markov chain that approximates in the sense of weak convergence a continuous-valued univariate Autoregressive process of first order is generated. It is a popular method used in economics and in finance.

The concept of reliable and clinically significant change (Jacobson & Truax, 1991) helps you answer the following questions for a sample with two measurements at different points in time (pre & post): Which proportion of my sample has a (considering the reliability of the instrument) probably not-just-by-chance difference in pre- vs. post-scores? Which proportion of my sample does not only change in a statistically significant way (see question one), but also in a clinically significant way (e.g. change from a test score regarded "dysfunctional" to a score regarded "functional")? This package allows you to very easily create a scatterplot of your sample in which the x-axis maps to the pre-scores, the y-axis maps to the post-scores and several graphical elements (lines, colors) allow you to gain a quick overview about reliable changes in these scores. An example of this kind of plot is Figure 2 of Jacobson & Truax (1991). Referenced article: Jacobson, N. S., & Truax, P. (1991) <doi:10.1037/0022-006X.59.1.12>.

This package provides a series of functions to call AD Model Builder (i.e., compile and run models) from within R, read the results back into R as admb objects, and provide standard accessors (i.e. coef(), vcov(), etc.).

Analyzes and predicts from matrix population models (Caswell 2006) <doi:10.1002/9781118445112.stat07481>.

This package provides functions to obtain an important number of electoral indicators described in the package, which can be divided into two large sections: The first would be the one containing the indicators of electoral disproportionality, such as, Rae index, Loosemoreâ Hanby index, etc. The second group is intended to study the dimensions of the party system vote, through the indicators of electoral fragmentation, polarization, volatility, etc. Moreover, multiple seat allocation simulations can also be performed based on different allocation systems, such as the D'Hondt method, Sainte-Laguë, etc. Finally, some of these functions have been built so that, if the user wishes, the data provided by the Spanish Ministry of Home Office for different electoral processes held in Spain can be obtained automatically. All the above will allow the users to carry out deep studies on the results obtained in any type of electoral process. The methods are described in: Oñate, Pablo and Ocaña, Francisco A. (1999, ISBN:9788474762815); Ruiz Rodrà guez, Leticia M. and Otero Felipe, Patricia (2011, ISBN:9788474766226).

This package provides a modified implementation of stepwise regression that greedily searches the space of interactions among features in order to build polynomial regression models. Furthermore, the hypothesis tests conducted are valid-post model selection due to the use of a revisiting procedure that implements an alpha-investing rule. As a result, the set of rejected sequential hypotheses is proven to control the marginal false discover rate. When not searching for polynomials, the package provides a statistically valid algorithm to run and terminate stepwise regression. For more information, see Johnson, Stine, and Foster (2019) <arXiv:1510.06322>.

Many packages in the r-dcm family take similar arguments, which are checked for expected structures and values. Rather than duplicating code across several packages, commonly used check functions are included here. This package can then be imported to access the check functions in other packages.