References and cites R and R packages on the fly in R Markdown and Quarto'. pakret provides a minimalistic API that generates preformatted citations of R and R packages, and adds their reference to a .bib file directly from within your document.

Generate power for the Cox proportional hazards model by simulating survival events data with time dependent exposure status for subjects. A dichotomous exposure variable is considered with a single transition from unexposed to exposed status during the subject's time on study.

This package contains functionality for regression standardization. Four general classes of models are allowed; generalized linear models, conditional generalized estimating equation models, Cox proportional hazards models and shared frailty gamma-Weibull models. Sjolander, A. (2016) <doi:10.1007/s10654-016-0157-3>.

This package performs inference for C of risk prediction models with censored survival data, using the method proposed by Uno et al. (2011) <doi:10.1002/sim.4154>. Inference for the difference in C between two competing prediction models is also implemented.

Model stacking is an ensemble technique that involves training a model to combine the outputs of many diverse statistical models, and has been shown to improve predictive performance in a variety of settings. stacks implements a grammar for tidymodels'-aligned model stacking.

This package provides a topological version of k-NN: An abstract model is build as 2-dimensional self-organising map. Samples of unknown class are predicted by mapping them on the SOM and analysing class membership of neurons in the neighbourhood.

Simulates regression models, including both simple regression and generalized linear mixed models with up to three level of nesting. Power simulations that are flexible allowing the specification of missing data, unbalanced designs, and different random error distributions are built into the package.

This package implements the truncated harmonic mean estimator (THAMES) of the reciprocal marginal likelihood using posterior samples and unnormalized log posterior values via reciprocal importance sampling. Metodiev, Perrot-Dockès, Ouadah, Irons, Latouche, & Raftery (2024). Bayesian Analysis. <doi:10.1214/24-BA1422>.

This package provides a global-local approximation framework for large-scale Gaussian process modeling. Please see Vakayil and Joseph (2024) <doi:10.1080/00401706.2023.2296451> for details. This work is supported by U.S. NSF grants CMMI-1921646 and DMREF-1921873.

This package provides methods for calculating the variance scale exponent to identify memory patterns in time series data. Includes tests for white noise, short memory, and long memory. See Fu, H. et al. (2018) <doi:10.1016/j.physa.2018.06.092>.

This package provides functions for the analysis of whole-genome sequencing studies to simultaneously detect the existence, and estimate the locations of association signals at genome-wide scale. The functions allow genome-wide association scan, candidate region scan and single window test.

This package contains the resample and windowfilter command line utilities. The resample command allows changing the sampling rate of a sound file, while the windowfilter command allows designing Finite Impulse Response (FIR) filters using the so-called window method.

This package generates interactive visualisations for analysis of RNA-sequencing data using output from limma, edgeR or DESeq2 packages in an HTML page. The interactions are built on top of the popular static representations of analysis results in order to provide additional information.

This package provides bindings to libsodium: a library for encryption, decryption, signatures, password hashing and more. Sodium uses curve25519, a Diffie-Hellman function by Daniel Bernstein, which has become very popular after it was discovered that the NSA had backdoored Dual EC DRBG.

This package provides a set of Shiny apps for effective communication and understanding in statistics. The current version includes properties of normal distribution, properties of sampling distribution, one-sample z and t tests, two samples independent (unpaired) t test and analysis of variance.

This package provides miscellaneous functions for SciViews or general use, including tools to manage a temporary environment attached to the search path for temporary variables you do not want to save() or load(); test the current platform; showing progress bars, etc.

This package implements the Python leidenalg module to be called in R. It enables clustering using the Leiden algorithm for partitioning a graph into communities. See also Traag et al (2018) "From Louvain to Leiden: guaranteeing well-connected communities." <arXiv:1810.08473>.

Quality Ensured Demonstrations (QED) is a test framework for Test Driven Development (TDD) and Behaviour Driven Development (BDD) utilizing Literate Programming techniques. QED sits somewhere between lower-level testing tools like Test::Unit and requirement specifications systems like Cucumber.

Multivariate optimal allocation for different domains in one and two stages stratified sample design. R2BEAT extends the Neyman (1934) â Tschuprow (1923) allocation method to the case of several variables, adopting a generalization of the Bethelâ s proposal (1989). R2BEAT develops this methodology but, moreover, it allows to determine the sample allocation in the multivariate and multi-domains case of estimates for two-stage stratified samples. It also allows to perform both Primary Stage Units and Secondary Stage Units selection. This package requires the availability of ReGenesees', that can be installed from <https://github.com/DiegoZardetto/ReGenesees>.

An implementation of the radviz projection in R. It enables the visualization of multidimensional data while maintaining the relation to the original dimensions. This package provides functions to create and plot radviz projections, and a number of summary plots that enable comparison and analysis. For reference see Hoffman *et al.* (1999) (<doi:10.1145/331770.331775>) for original implementation, see Di Caro *et al* (2012) (<doi:10.1007/978-3-642-13672-6_13>), for the original method for dimensional anchor arrangements, see Demsar *et al.* (2007) (<doi:10.1016/j.jbi.2007.03.010>) for the original Freeviz implementation.

This package provides a convenient R wrapper to the Comet API, which is a cloud platform allowing you to track, compare, explain and optimize machine learning experiments and models. Experiments can be viewed on the Comet online dashboard at <https://www.comet.com>.

DNA copy number data evaluation using both their initial form (copy number as a noisy function of genomic position) and their approximation by a piecewise-constant function (segmentation), for the purpose of identifying genomic regions where the copy number differs from the norm.

Implementation of estimators for inferring the mean of censored cost data. Including the estimators BT from Bang and Tsiatis (2000) <doi:10.1093/biomet/87.2.329> and ZT from Zhao and Tian (2001) <doi:10.1111/j.0006-341X.2001.01002.x>.

Several tests for differential methylation in methylation array data, including one-sided differential mean and variance test. Methods used in the package refer to Dai, J, Wang, X, Chen, H and others (2021) "Incorporating increased variability in discovering cancer methylation markers", Biostatistics, submitted.