Recursive display of names and paths of all the items nested within sublists of a list object.

Direct insertion of over 1000 symbols (e.g. currencies, letters, emojis, arrows, mathematical symbols and so on) into Rmarkdown documents and Shiny applications by incorporating HTML hex codes.

This package provides a set of tools to explore the behaviour statistics used for forensic DNA interpretation when close relatives are involved. The package also offers some useful tools for exploring other forensic DNA situations.

Transfer REDCap (Research Electronic Data Capture) data to a database, specifically optimized for DuckDB'. Processes data in chunks to handle large datasets without exceeding available memory. Features include data labeling, coded value conversion, and hearing a "quack" sound on success.

Create and combine HTML and PDF reports from within R. Possibility to design tables and listings for reporting and also include R plots.

Conversion between attitude representations: DCM, Euler angles, Quaternions, and Euler vectors. Plus conversion between 2 Euler angle set types (xyx, yzy, zxz, xzx, yxy, zyz, xyz, yzx, zxy, xzy, yxz, zyx). Fully vectorized code, with warnings/errors for Euler angles (singularity, out of range, invalid angle order), DCM (orthogonality, not proper, exceeded tolerance to unity determinant) and Euler vectors(not unity). Also quaternion and other useful functions. Based on SpinCalc by John Fuller and SpinConv by Paolo de Leva.

Automatic open data acquisition from resources of Polish Head Office of Geodesy and Cartography ('GŠówny UrzÄ d Geodezji i Kartografii') (<https://www.gov.pl/web/gugik>). Available datasets include various types of numeric, raster and vector data, such as orthophotomaps, digital elevation models (digital terrain models, digital surface model, point clouds), state register of borders, spatial databases, geometries of cadastral parcels, 3D models of buildings, and more. It is also possible to geocode addresses or objects using the geocodePL_get() function.

This package provides a collection of HTML', JavaScript', CSS and fonts assets that generate Redoc documentation from an OpenAPI Specification: <https://redocly.com/redoc/>.

Bayesian regression with functional data, including regression with scalar, survival, or functional outcomes. The package allows regression with scalar and functional predictors. Methods are described in Jiang et al. (2025) "Tutorial on Bayesian Functional Regression Using Stan" <doi:10.1002/sim.70265>.

This package performs penalized quantile regression with LASSO, elastic net, SCAD and MCP penalty functions including group penalties. In addition, offers a group penalty that provides consistent variable selection across quantiles. Provides a function that automatically generates lambdas and evaluates different models with cross validation or BIC, including a large p version of BIC. Below URL provides a link to article in the R Journal.

This package provides read and write support for the Conic Benchmark Format (CBF, version 4) within the R Optimization Infrastructure ('ROI'). Supported cone types include the positive orthant, second-order (SOC), rotated second-order (bridged automatically to standard SOC), exponential (primal and dual), power (primal and dual), and semidefinite (symmetric-vectorised) cones, as well as their mixed-integer variants. The reader translates a .cbf file into an ROI OP object, handling coordinate-convention differences between CBF and ROI transparently; the writer serialises an ROI OP object back to CBF plain-text.

Scalable methods for learning causal graphical models from mixed data, including continuous, discrete, and censored variables. The package implements CausalMGM, which combines a convex, score-based approach for learning an initial moralized graph with a producer-consumer scheme that enables efficient parallel conditional independence testing in constraint-based causal discovery algorithms. The implementation supports high-dimensional datasets and provides individual access to core components of the workflow, including MGM and the PC-Stable and FCI-Stable causal discovery algorithms. To support practical applications, the package includes multiple model selection strategies, including information criteria based on likelihood and model complexity, cross-validation for out-of-sample likelihood estimation, and stability-based approaches that assess graph robustness across subsamples.

This package provides functions and datasets required for the ST 370 course at North Carolina State University.

Computes confidence intervals for nonlinear functions of model parameters (e.g., product of k coefficients) in single-level and multilevel structural equation models. Methods include the distribution of the product, Monte Carlo simulation, and bootstrap methods. It also performs the Model-Based Constrained Optimization (MBCO) procedure for hypothesis testing of indirect effects. References: Tofighi, D., and MacKinnon, D. P. (2011). RMediation: An R package for mediation analysis confidence intervals. Behavior Research Methods, 43, 692-700. <doi:10.3758/s13428-011-0076-x>; Tofighi, D., and Kelley, K. (2020). Improved inference in mediation analysis: Introducing the model-based constrained optimization procedure. Psychological Methods, 25(4), 496-515. <doi:10.1037/met0000259>; Tofighi, D. (2020). Bootstrap Model-Based Constrained Optimization Tests of Indirect Effects. Frontiers in Psychology, 10, 2989. <doi:10.3389/fpsyg.2019.02989>.

High resolution vector country boundaries derived from Natural Earth data, can be plotted in rworldmap.

Casting metadata for REDCap database creation and handling of castellated data using repeated instruments and longitudinal projects in REDCap'. Keeps a focused data export approach, by allowing to only export required data from the database. Also for casting new REDCap databases based on datasets from other sources. Originally forked from the R part of REDCapRITS by Paul Egeler. See <https://github.com/pegeler/REDCapRITS>. REDCap (Research Electronic Data Capture) is a secure, web-based software platform designed to support data capture for research studies, providing 1) an intuitive interface for validated data capture; 2) audit trails for tracking data manipulation and export procedures; 3) automated export procedures for seamless data downloads to common statistical packages; and 4) procedures for data integration and interoperability with external sources (Harris et al (2009) <doi:10.1016/j.jbi.2008.08.010>; Harris et al (2019) <doi:10.1016/j.jbi.2019.103208>).

This package provides a novel generalized Random Forest method, that can improve on RFs by borrowing the strength of penalized parametric regression. Based on Zhang et al. (2019) <doi:10.48550/arXiv.1904.10416>.

Base S4-classes and functions for robust asymptotic statistics.

Plots the Receiver Operating Characteristics Surface for high-throughput class-skewed data, calculates the Volume under the Surface (VUS) and the FDR-Controlled Area Under the Curve (FCAUC), and conducts tests to compare two ROC surfaces. Computes eROC curve and the corresponding AUC for imperfect reference standard.

This package creates interactive graphs with R'. It joins the data analysis power of R and the visualization libraries of JavaScript in one package.

This package provides a set of functions to generate, access and analyze standard data products from archival tagging data.

Interface to the ChEA3 transcription factor enrichment API. ChEA3 integrates evidence from ChIP-seq, co-expression, and literature resources to prioritize transcription factors regulating a given set of genes. This package provides convenient R functions to query the API, retrieve ranked results across collections (including integrated scores), and standardize output for downstream analysis in R/Bioconductor workflows. See <https://maayanlab.cloud/chea3/> or Keenan (2019) <doi:10.1093/nar/gkz446> for further details.

Visualize networks using the javascript library roughjs'. This allows to draw sketchy, hand-drawn-like networks.

This package provides a collection of several utility functions related to resolvable and affine resolvable Partially Balanced Incomplete Block Designs (PBIBDs), have been developed. In the class of resolvable designs, affine resolvable designs are said to be optimal, Bailey (1995) <doi:10.2307/2337638>. Here, the package contains three functions to generate and study the characterization properties of these designs. Developed functions are named as PBIBD1(), PBIBD2() and PBIBD3(), in which first two functions are used to generate two new series of affine resolvable PBIBDs and last one is used to generate a new series of resolvable PBIBDs, respectively. In addition, these functions can also be used to generate design parameters (v, b, r and k), canonical efficiency factors, variance factor between associates and average variance factors of the generated designs. Here v is the number of treatments, b (= b1 + b2, in case of non-proper design) is the number of blocks, r is the number of replications and k (= k1 + k2; k1 is the size of b1 and k2 is the size of b2) is the block size.