This package provides subsets with reference semantics, i.e. subsets which automatically reflect changes in the original object, and which optionally update the original object when they are changed.

This package implements simple Hamiltonian Monte Carlo routines in R for sampling from any desired target distribution which is continuous and smooth. See Neal (2017) <arXiv:1701.02434> for further details on Hamiltonian Monte Carlo. Automatic parameter selection is not supported.

This package provides R6 classes, methods and utilities to construct, analyze, summarize, and visualize regression models.

This is a sudoku game package with a shiny application for playing .

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'.

This package provides methods and tools for implementing functional singular spectrum analysis and related techniques.

This package provides functions for the complete analysis of respiratory data. Consists of a set of functions that allow to preprocessing respiratory data, calculate both regular statistics and nonlinear statistics, conduct group comparison and visualize the results. Especially, Power Spectral Density ('PSD') (A. Eke (2000) <doi:10.1007/s004249900135>), MultiScale Entropy(MSE) ('Madalena Costa(2002) <doi:10.1103/PhysRevLett.89.068102>) and MultiFractal Detrended Fluctuation Analysis(MFDFA) ('Jan W.Kantelhardt (2002) <doi:10.1016/S0378-4371(02)01383-3>) were applied for the analysis of respiratory data.

Provide reproducible R chunks in R Markdown document that automatically check computational results for reproducibility. This is achieved by creating json files storing metadata about computational results. A comprehensive tutorial to the package is available as preprint by Brandmaier & Peikert (2024, <doi:10.31234/osf.io/3zjvf>).

Connector to the REST API of a Rock R server, to perform operations on a remote R server session, or administration tasks. See Rock documentation at <https://rockdoc.obiba.org/>.

To facilitate using cereal with R via cpp11 or Rcpp'. cereal is a header-only C++11 serialization library. cereal takes arbitrary data types and reversibly turns them into different representations, such as compact binary encodings, XML', or JSON'. cereal was designed to be fast, light-weight, and easy to extend - it has no external dependencies and can be easily bundled with other code or used standalone. Please see <https://uscilab.github.io/cereal/> for more information.

Access to some of the C level functions of the xts package. In its current state, the package is mostly a proof-of-concept to support adding useful functions, and does not yet add any of its own.

This package provides a useful statistical tool for the construction and analysis of Honeycomb Selection Designs. More information about this type of designs: Fasoula V. (2013) <doi:10.1002/9781118497869.ch6> Fasoula V.A., and Tokatlidis I.S. (2012) <doi:10.1007/s13593-011-0034-0> Fasoulas A.C., and Fasoula V.A. (1995) <doi:10.1002/9780470650059.ch3> Tokatlidis I. (2016) <doi:10.1017/S0014479715000150> Tokatlidis I., and Vlachostergios D. (2016) <doi:10.3390/d8040029>.

Communications simulation package supporting forward error correction.

Facilitating the creation of reproducible statistical report templates. Once created, rapport templates can be exported to various external formats (HTML, LaTeX, PDF, ODT etc.) with pandoc as the converter backend.

Converts LESS to CSS. It uses V8 engine, where LESS parser is run. Functions for LESS text, file or folder conversion are provided. This work was supported by a junior grant research project by Czech Science Foundation GACR no. GJ18-04150Y'.

Fit statistical models based on the Dawid-Skene model - Dawid and Skene (1979) <doi:10.2307/2346806> - to repeated categorical rating data. Full Bayesian inference for these models is supported through the Stan modelling language. rater also allows the user to extract and plot key parameters of these models.

This package provides a methodology to perform multivariate measurement error adjustment using external validation data. Allows users to remove the attenuating effect of measurement error by incorporating a distribution of external validation data, and allows for plotting of all resultant adjustments. Sensitivity analyses can also be run through this package to test how different ranges of validity coefficients can impact the effect of the measurement error adjustment. The methods implemented in this package are based on the work by Muoka, A., Agogo, G., Ngesa, O., Mwambi, H. (2020): <doi:10.12688/f1000research.27892.1>.

Autoencoding Random Forests ('RFAE') provide a method to autoencode mixed-type tabular data using Random Forests ('RF'), which involves projecting the data to a latent feature space of user-chosen dimensionality (usually a lower dimension), and then decoding the latent representations back into the input space. The encoding stage is useful for feature engineering and data visualisation tasks, akin to how principal component analysis ('PCA') is used, and the decoding stage is useful for compression and denoising tasks. At its core, RFAE is a post-processing pipeline on a trained random forest model. This means that it can accept any trained RF of ranger object type: RF', URF or ARF'. Because of this, it inherits Random Forests robust performance and capacity to seamlessly handle mixed-type tabular data. For more details, see Vu et al. (2025) <doi:10.48550/arXiv.2505.21441>.

Focused on linear, quadratic and cubic regression models, it has a function for calculating the models, obtaining a list with their parameters, and a function for making the graphs for the respective models.

Build native Windows desktop applications using R and WebView2'. Provides a robust R6'-based event loop, asynchronous background task management via mirai and callr', and a native Win32 message bridge for seamless R'-to-user-interface communication without listening ports or network overhead. Allows R developers to create professional, standalone desktop tools with modern web-based user interfaces while maintaining a pure R backend.

This package provides a tool to conquer the difficulties to convert various region names and administration division codes of Chinese regions. The current version enables seamlessly converting Chinese regions formal names, common-used names, and codes between each other at the city level from 1986 to 2019.

This package provides data structures and functions for file input/output in the ribios software suite, supporting common bioinformatics and computational biology file formats, designed for fast loading and high performance with minimal dependencies.

An implementation of robust bent line regression. It can fit the bent line regression and test the existence of change point, for the paper, "Feipeng Zhang and Qunhua Li (2016). Robust bent line regression, submitted.".

Algorithms for the spatial stratification of landscapes, sampling and modeling of spatially-varying phenomena. These algorithms offer a simple framework for the stratification of geographic space based on raster layers representing landscape factors and/or factor scales. The stratification process follows a hierarchical approach, which is based on first level units (i.e., classification units) and second-level units (i.e., stratification units). Nonparametric techniques allow to measure the correspondence between the geographic space and the landscape configuration represented by the units. These correspondence metrics are useful to define sampling schemes and to model the spatial variability of environmental phenomena. The theoretical background of the algorithms and code examples are presented in Fuentes et al. (2022). <doi:10.32614/RJ-2022-036>.