Estimates previously compiled state-space modeling for mouse-tracking experiments using the rstan package, which provides the R interface to the Stan C++ library for Bayesian estimation.

Utility functions for spectroscopy. 1. Functions to simulate spectra for use in teaching or testing. 2. Functions to process files created by LoggerPro and SpectraSuite software.

An dual-paradigm interface to Supabase (<https://supabase.com/>), an open-source backend-as-a-service platform. Provides comprehensive database operations including Create, Read, Update, Delete ('CRUD') functionality through both REST API endpoints and direct PostgreSQL database connections. Simplifies authentication, data management, and schema operations for Supabase projects.

Builds, evaluates and validates a nomogram with survey data and right-censored outcomes. As described in Capanu (2015) <doi:10.18637/jss.v064.c01>, the package contains functions to create the nomogram, validate it using bootstrap, as well as produce the calibration plots.

This package implements sparse Bayesian learning method for QTL mapping and genome-wide association studies.

This package implements the SparseStep model for solving regression problems with a sparsity constraint on the parameters. The SparseStep regression model was proposed in Van den Burg, Groenen, and Alfons (2017) <arXiv:1701.06967>. In the model, a regularization term is added to the regression problem which approximates the counting norm of the parameters. By iteratively improving the approximation a sparse solution to the regression problem can be obtained. In this package both the standard SparseStep algorithm is implemented as well as a path algorithm which uses golden section search to determine solutions with different values for the regularization parameter.

Split Knockoff is a data adaptive variable selection framework for controlling the (directional) false discovery rate (FDR) in structural sparsity, where variable selection on linear transformation of parameters is of concern. This proposed scheme relaxes the linear subspace constraint to its neighborhood, often known as variable splitting in optimization. Simulation experiments can be reproduced following the Vignette. Split Knockoffs is first defined in Cao et al. (2021) <doi:10.48550/arXiv.2103.16159>.

Assesses the number of concurrent users shiny applications are capable of supporting, and for directing application changes in order to support a higher number of users. Provides facilities for recording shiny application sessions, playing recorded sessions against a target server at load, and analyzing the resulting metrics.

Convert a time series of observations to a time series of standardised indices that can be used to monitor variables on a common and probabilistically interpretable scale. The indices can be aggregated and rescaled to different time scales, visualised using plot capabilities, and calculated using a range of distributions. This includes flexible non-parametric and non-stationary methods.

This package provides utilities to create or suppress start-up messages.

This package provides functions for creating, displaying, and evaluating stopping rules for safety monitoring in clinical studies.

Simulates and plots quantities of interest (relative hazards, first differences, and hazard ratios) for linear coefficients, multiplicative interactions, polynomials, penalised splines, and non-proportional hazards, as well as stratified survival curves from Cox Proportional Hazard models. It also simulates and plots marginal effects for multiplicative interactions. Methods described in Gandrud (2015) <doi:10.18637/jss.v065.i03>.

Latent repeated measures ANOVA (L-RM-ANOVA) is a structural equation modeling based alternative to traditional repeated measures ANOVA. L-RM-ANOVA extends the latent growth components approach by Mayer et al. (2012) <doi:10.1080/10705511.2012.713242> and introduces latent variables to repeated measures analysis.

Dual interfaces, graphical and programmatic, designed for intuitive applications of Multilevel Regression and Poststratification (MRP). Users can apply the method to a variety of datasets, from electronic health records to sample survey data, through an end-to-end Bayesian data analysis workflow. The package provides robust tools for data cleaning, exploratory analysis, flexible model building, and insightful result visualization. For more details, see Si et al. (2020) <https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2020002/article/00003-eng.pdf?st=iF1_Fbrh> and Si (2025) <doi:10.1214/24-STS932>.

This package provides a consistent interface to encrypt and decrypt strings, R objects and files using symmetric and asymmetric key encryption.

This package contains an R Markdown template for a clinical trial protocol adhering to the SPIRIT statement. The SPIRIT (Standard Protocol Items for Interventional Trials) statement outlines recommendations for a minimum set of elements to be addressed in a clinical trial protocol. Also contains functions to create a xml document from the template and upload it to clinicaltrials.gov<https://www.clinicaltrials.gov/> for trial registration.

Extract glyph information from font data, and translate the outline curves to flattened paths or tessellated polygons. The converted data is returned as a data.frame in easy-to-plot format.

This package provides an R and shiny interface to the Web Awesome component library. The package is generator-driven, exposing Web Awesome web components as R functions that produce HTML tags and integrate with the reactive model that shiny uses.

This package provides tools for spatial data analysis. Emphasis on kriging. Provides functions for prediction and simulation. Intended to be relatively straightforward, fast, and flexible.

This package provides methods to detect structural changes in time series or random fields (spatial data). Focus is on the detection of abrupt changes or trends in independent data, but the package also provides a function to de-correlate data with dependence. The functions are based on the test suggested in Schmidt (2024) <DOI:10.3150/23-BEJ1686> and the work in Görz and Fried (2025) <DOI:10.48550/arXiv.2512.11599>.

Collection of datasets from Sen & Srivastava: "Regression Analysis, Theory, Methods and Applications", Springer. Sources for individual data files are more fully documented in the book.

Provide regularized maximum covariance analysis incorporating smoothness, sparseness and orthogonality of couple patterns by using the alternating direction method of multipliers algorithm. The method can be applied to either regularly or irregularly spaced data, including 1D, 2D, and 3D (Wang and Huang, 2018 <doi:10.1002/env.2481>).

This package provides a set of spatial accessibility measures from a set of locations (demand) to another set of locations (supply). It aims, among others, to support research on spatial accessibility to health care facilities. Includes the locations and some characteristics of major public hospitals in Greece.

Estimates split-half reliabilities for scoring algorithms of cognitive tasks and questionnaires. The splithalfr supports researcher-provided scoring algorithms, with six vignettes illustrating how on included datasets. The package provides four splitting methods (first-second, odd-even, permutated, Monte Carlo), the option to stratify splits by task design, a number of reliability coefficients, the option to sub-sample data, and bootstrapped confidence intervals.