Statistical distribution in OOP (Object Oriented Programming) way. This package proposes a R6 class interface to classic statistical distribution, and new distributions can be easily added with the class AbstractDist. A useful point is the generic fit() method for each class, which uses a maximum likelihood estimation to find the parameters of a dataset, see, e.g. Hastie, T. and al (2009) <isbn:978-0-387-84857-0>. Furthermore, the rv_histogram class gives a non-parametric fit, with the same accessors that for the classic distribution. Finally, three random generators useful to build synthetic data are given: a multivariate normal generator, an orthogonal matrix generator, and a symmetric positive definite matrix generator, see Mezzadri, F. (2007) <arXiv:math-ph/0609050>.

This package provides a collection of functions for basic database and document management operations such as add, get, list access or delete. Every cdbFunction() gets and returns a list() containing the connection setup. Such a list can be generated by cdbIni().

Queries data from RDAP servers.

Computation of (direct and indirect) revealed preferences, fast non-parametric tests of rationality axioms (WARP, SARP, GARP), simulation of axiom-consistent data, and detection of axiom-consistent subpopulations. Rationality tests follow Varian (1982) <doi:10.2307/1912771>, axiom-consistent subpopulations follow Crawford and Pendakur (2012) <doi:10.1111/j.1468-0297.2012.02545.x>.

The getconf command-line tool provided by libc allows querying of a large number of system variables. This package provides similar functionality.

This package provides simplified methods for managing classic Rubik's cubes and many other modifications of it (such as NxNxN size cubes, void cubes and 8-coloured cubes - so called octa cubes). Includes functions of handling special syntax for managing such cubes; and different approach to plotting 3D cubes without using external libraries (for example OpenGL').

The Radiant Model menu includes interfaces for linear and logistic regression, naive Bayes, neural networks, classification and regression trees, model evaluation, collaborative filtering, decision analysis, and simulation. The application extends the functionality in radiant.data'.

This package provides a simple and efficient way to read data from Paradox database files (.db) directly into R as modern tibble data frames. It uses the underlying pxlib C library, to handle the low-level file format details and provides a clean, user-friendly R interface.

Robust covariance estimation for matrix-valued data and data with Kronecker-covariance structure using the Matrix Minimum Covariance Determinant (MMCD) estimators and outlier explanation using and Shapley values.

Oracle Database interface (DBI) driver for R. This is a DBI-compliant Oracle driver based on the OCI.

We introduce a robust matrix factor model that explicitly incorporates tail behavior and employs a mean-shift term to avoid efficiency losses through pre-centering of observed matrices. More details on the methods related to our paper are currently under submission. A full reference to the paper will be provided in future versions once the paper is published.

The cnpy library written by Carl Rogers provides read and write facilities for files created with (or for) the NumPy extension for Python'. Vectors and matrices of numeric types can be read or written to and from files as well as compressed files. Support for integer files is available if the package has been built with as C++11 which should be the default on all platforms since the release of R 3.3.0.

Computes a novel variable importance for random forests: Impurity reduction importance scores for out-of-bag (OOB) data complementing the existing inbag Gini importance, see also <doi: 10.1080/03610926.2020.1764042>. The Gini impurities for inbag and OOB data are combined in three different ways, after which the information gain is computed at each split. This gain is aggregated for each split variable in a tree and averaged across trees.

This package implements full Bayesian analysis for calibrating mathematical models with new methodology for modeling the discrepancy function. It allows for emulation, calibration and prediction using complex mathematical model outputs and experimental data. See the reference: Mengyang Gu and Long Wang, 2018, Journal of Uncertainty Quantification; Mengyang Gu, Fangzheng Xie and Long Wang, 2022, Journal of Uncertainty Quantification; Mengyang Gu, Kyle Anderson and Erika McPhillips, 2023, Technometrics.

Nuclear Decay Data for Dosimetric Calculations from the International Commission on Radiological Protection from ICRP Publication 107. Ann. ICRP 38 (3). Eckerman, Keith and Endo, Akira 2008 <doi:10.1016/j.icrp.2008.10.004> <https://www.icrp.org/publication.asp?id=ICRP%20Publication%20107>. This is a database of the physical data needed in calculations of radionuclide-specific protection and operational quantities. The data is prescribed by the ICRP, the international authority on radiation dose standards, for estimating dose from the intake of or exposure to radionuclides in the workplace and the environment. The database contains information on the half-lives, decay chains, and yields and energies of radiations emitted in nuclear transformations of 1252 radionuclides of 97 elements.

The analysis of different aspects of biodiversity requires specific algorithms. For example, in regionalisation analyses, the high frequency of ties and zero values in dissimilarity matrices produced by Beta-diversity turnover produces hierarchical cluster dendrograms whose topology and bootstrap supports are affected by the order of rows in the original matrix. Moreover, visualisation of biogeographical regionalisation can be facilitated by a combination of hierarchical clustering and multi-dimensional scaling. The recluster package provides robust techniques to visualise and analyse patterns of biodiversity and to improve occurrence data for cryptic taxa.

Client for the web service methods provided by DataCite (<https://www.datacite.org/>), including functions to interface with their RESTful search API. The API is backed by Elasticsearch', allowing expressive queries, including faceting.

These functions take a character vector as input, identify and cluster similar values, and then merge clusters together so their values become identical. The functions are an implementation of the key collision and ngram fingerprint algorithms from the open source tool Open Refine <https://openrefine.org/>. More info on key collision and ngram fingerprint can be found here <https://openrefine.org/docs/technical-reference/clustering-in-depth>.

Minimally adjust the values of numerical records in a data.frame, such that each record satisfies a predefined set of equality and/or inequality constraints. The constraints can be defined using the validate package. The core algorithms have recently been moved to the lintools package, refer to lintools for a more basic interface and access to a version of the algorithm that works with sparse matrices.

Estimates life tables, specifically (crude) death rates and (raw and graduated) death probabilities, using rolling windows in one (e.g., age), two (e.g., age and time) or three (e.g., age, time and income) dimensions. The package can also be utilised for summarising statistics and smoothing continuous variables through rolling windows in other domains, such as estimating averages of self-positioning ideology in political science. Acknowledgements: The authors wish to thank Ministerio de Ciencia, Innovación y Universidades (grant PID2021-128228NB-I00) and Generalitat Valenciana (grants HIECPU/2023/2, Conselleria de Hacienda, Economà a y Administración Pública, and CIGE/2023/7, Conselleria de Educación, Cultura, Universidades y Empleo) for supporting this research.

Robust estimators for generalized ratio model (Wada, Sakashita and Tsubaki, 2021)<doi:10.17713/ajs.v50i1.994> and linear regression model by the IRLS(iterative reweighted least squares) algorithm are contained.

This package provides XML parsing capability through the Rapidxml C++ header-only library.

CausalEGM is a general causal inference framework for estimating causal effects by encoding generative modeling, which can be applied in both discrete and continuous treatment settings. A description of the methods is given in Liu (2022) <arXiv:2212.05925>.

Create plots and LaTeX tables that look like SPSS output for use in teaching materials. Rather than copying-and-pasting SPSS output into documents, R code that mocks up SPSS output can be integrated directly into dynamic LaTeX documents with tools such as knitr. Functionality includes statistical techniques that are typically covered in introductory statistics classes: descriptive statistics, common hypothesis tests, ANOVA, and linear regression, as well as box plots, histograms, scatter plots, and line plots (including profile plots).