This package provides tools to convert the output of segmentation analysis using DNAcopy to a matrix structure with overlapping segments as rows and samples as columns so that other computational analyses can be applied to segmented data.

Melissa is a Baysian probabilistic model for jointly clustering and imputing single cell methylomes. This is done by taking into account local correlations via a Generalised Linear Model approach and global similarities using a mixture modelling approach.

This package provides an R interface for various subsampling algorithms implemented in python packages. Currently, interfaces to the geosketch and scSampler python packages are implemented. In addition it also provides diagnostic plots to evaluate the subsampling.

With this package it is possible to define parameter spaces, constraints and dependencies for arbitrary algorithms, and to program on such spaces. It also includes statistical designs and random samplers. Objects are implemented as R6 classes.

This package provides functions to train self-organising maps (SOMs). Also interrogation of the maps and prediction using trained maps are supported. The name of the package refers to Teuvo Kohonen, the inventor of the SOM.

This package provides a pure Rust implementation of the NIST P-256 (a.k.a. secp256r1, prime256v1) elliptic curve as defined in SP 800-186, with support for ECDH, ECDSA signing/verification, and general purpose curve arithmetic.

This package provides a pure Rust implementation of the NIST P-384 (a.k.a. secp384r1) elliptic curve as defined in SP 800-186 with support for ECDH, ECDSA signing/verification, and general purpose curve arithmetic support.

Loom is a testing tool for concurrent Rust code. It runs a test many times, permuting the possible concurrent executions of that test under the C11 memory model. It uses state reduction techniques to avoid combinatorial explosion.

Loom is a testing tool for concurrent Rust code. It runs a test many times, permuting the possible concurrent executions of that test under the C11 memory model. It uses state reduction techniques to avoid combinatorial explosion.

Loom is a testing tool for concurrent Rust code. It runs a test many times, permuting the possible concurrent executions of that test under the C11 memory model. It uses state reduction techniques to avoid combinatorial explosion.

This package provides a Rust library for parsing and generating Intel HEX (or IHEX) objects. This format is commonly used for representing compiled program code and data to be loaded into a microcontroller, flash memory or ROM.

Loom is a testing tool for concurrent Rust code. It runs a test many times, permuting the possible concurrent executions of that test under the C11 memory model. It uses state reduction techniques to avoid combinatorial explosion.

Loom is a testing tool for concurrent Rust code. It runs a test many times, permuting the possible concurrent executions of that test under the C11 memory model. It uses state reduction techniques to avoid combinatorial explosion.

Loom is a testing tool for concurrent Rust code. It runs a test many times, permuting the possible concurrent executions of that test under the C11 memory model. It uses state reduction techniques to avoid combinatorial explosion.

The regression discontinuity (RD) design is a popular quasi-experimental design for causal inference and policy evaluation. The rdmulti package provides tools to analyze RD designs with multiple cutoffs or scores: rdmc() estimates pooled and cutoff specific effects for multi-cutoff designs, rdmcplot() draws RD plots for multi-cutoff designs and rdms() estimates effects in cumulative cutoffs or multi-score designs. See Cattaneo, Titiunik and Vazquez-Bare (2020) <https://rdpackages.github.io/references/Cattaneo-Titiunik-VazquezBare_2020_Stata.pdf> for further methodological details.

This package provides functions to assist in performing probabilistic record linkage and deduplication: generating pairs, comparing records, em-algorithm for estimating m- and u-probabilities (I. Fellegi & A. Sunter (1969) <doi:10.1080/01621459.1969.10501049>, T.N. Herzog, F.J. Scheuren, & W.E. Winkler (2007), "Data Quality and Record Linkage Techniques", ISBN:978-0-387-69502-0), forcing one-to-one matching. Can also be used for pre- and post-processing for machine learning methods for record linkage. Focus is on memory, CPU performance and flexibility.

This package provides a portable Shiny tool to explore patient-level electronic health record data and perform chart review in a single integrated framework. This tool supports browsing clinical data in many different formats including multiple versions of the OMOP common data model as well as the MIMIC-III data model. In addition, chart review information is captured and stored securely via the Shiny interface in a REDCap (Research Electronic Data Capture) project using the REDCap API. See the ReviewR website for additional information, documentation, and examples.

This package provides a client for cryptocurrency exchange BitMEX <https://www.bitmex.com/> including the ability to obtain historic trade data and place, edit and cancel orders. BitMEX's Testnet and live API are both supported.

Posterior distribution in the Black-Litterman model is computed from a prior distribution given in the form of a time series of asset returns and a continuous distribution of views provided by the user as an external function.

Data sets of the Spanish National Forest Inventory <https://www.miteco.gob.es/es/biodiversidad/servicios/banco-datos-naturaleza/informacion-disponible.html> are processed to compute tree metrics and statistics. Function metrics2Vol() controls most of the routines.

Preprocessing tools and biodiversity measures (species abundance, species richness, population heterogeneity and sensitivity) for analysing marine benthic data. See Van Loon et al. (2015) <doi:10.1016/j.seares.2015.05.002> for an application of these tools.

An investigative tool designed to help users visualize correlations between variables in their datasets. This package aims to provide an easy and effective way to explore and visualize these correlations, making it easier to interpret and communicate results.

Converts any word, sentence or speech into Trump's infamous "covfefe" format. Reference: <https://www.nytimes.com/2017/05/31/us/politics/covfefe-trump-twitter.html>. Inspiration thanks to: <https://codegolf.stackexchange.com/questions/123685/covfefify-a-string>.

Utilities to make your clinical collaborations easier if not fun. It contains functions for designing studies such as Simon 2-stage and group sequential designs and for data analysis such as Jonckheere-Terpstra test and estimating survival quantiles.