WebAssembly Micro Runtime (WAMR) is a lightweight standalone WebAssembly (Wasm) runtime with small footprint, high performance and highly configurable features for applications cross from embedded, IoT, edge to Trusted Execution Environment (TEE), smart contract, cloud native and other features.

This package implements nonparametric bootstrap tests for detecting monotonicity in regression functions from Hall, P. and Heckman, N. (2000) <doi:10.1214/aos/1016120363> Includes tools for visualizing results using Nadaraya-Watson kernel regression and supports efficient computation with C++'.

This package aims to simplify the writing process, especially for Dutch legal authors. It has also been implemented in English and can be expanded to include other languages. The package offers macros for typical legal structures and contains a referencing system.

Frequentist confidence analysis answers the question: How confident are we in a particular treatment effect? This package calculates the frequentist confidence in a treatment effect of interest given observed data, and returns the family of confidence curves associated with that data.

For those wishing to interact with the Charles Schwab Individual Trader API (<https://developer.schwab.com/products/trader-api--individual>) with R in a simplified manner, this package offers wrapper functions around authentication and the available API calls to streamline the process.

This package provides a comprehensive tool for converting and retrieving the miRNA Name, Accession, Sequence, Version, History and Family information in different miRBase versions. It can process a huge number of miRNAs in a short time without other depends.

Regression models can be fitted for multiple outcomes simultaneously. This package computes estimates of parameters across fitted models and returns the matrix of asymptotic covariance. Various applications of this package, including CUPED (Controlled Experiments Utilizing Pre-Experiment Data), multiple comparison adjustment, are illustrated.

This package provides tools to create a layout for figures made of multiple panels, and to fill the panels with base, lattice', ggplot2 and ComplexHeatmap plots, grobs, as well as content from all image formats supported by ImageMagick (accessed through magick').

Defines a graphics device and functions for graphical output in terminal emulators that support graphical output. Currently terminals that support the Terminal Graphics Protocol (<https://sw.kovidgoyal.net/kitty/graphics-protocol/>) and terminal supporting Sixel (<https://en.wikipedia.org/wiki/Sixel>) are supported.

Colon normal tissue and cancer samples used in Corrada Bravo, et al. gene expression anti-profiles paper: BMC Bioinformatics 2012, 13:272 doi:10.1186/1471-2105-13-272. Measurements are z-scores obtained from the GeneExpression Barcode in the frma package.

Unlike other tools that dynamically link to the Cairo stack, freetypeharfbuzz is statically linked to specific versions of the FreeType and harfbuzz libraries. This ensures deterministic computation of text box extents for situations where reproducible results are crucial (for instance unit tests of graphics).

This package is a collection of search spaces for hyperparameter optimization in the mlr3 ecosystem. It features ready-to-use search spaces for many popular machine learning algorithms. The search spaces are from scientific articles and work for a wide range of data sets.

This package allows simple reflection of expressions containing variables. Reflection here means that a Haskell expression is turned into a string. The primary aim of this package is teaching and understanding; there are no options for manipulating the reflected expressions beyond showing them.

When writing a large manuscript, it is sometimes beneficial to repeat a theorem (or lemma or...) at an earlier or later point for didactic purposes. Unlike thmtools, this package allows replicating theorems not only in the same document, but in any other file.

Fits mixtures of multivariate contaminated normal distributions (with eigen-decomposed scale matrices) via the expectation conditional- maximization algorithm under a clustering or classification paradigm Methods are described in Antonio Punzo, Angelo Mazza, and Paul D McNicholas (2018) <doi:10.18637/jss.v085.i10>.

This package provides tools for simplifying the creation and management of data structures suitable for dealing with policy portfolios, that is, two-dimensional spaces of policy instruments and policy targets. The package also allows to generate measures of portfolio characteristics and facilitates their visualization.

This package contains pre-built human (GPL571) databases of gene expression profiles. The gene expression data was downloaded from NCBI GEO and preprocessed and normalized consistently. The biological context of each sample was recorded and manually verified based on the sample description in GEO.

This Python library is a wrapper around tokenize from the Python standard library. It provides two additional tokens ESCAPED_NL and UNIMPORTANT_WS, and a Token data type. Use src_to_tokens and tokens_to_src to roundtrip.

The package generalises the macro patching commands provided by P. Lehmann's etoolbox. The difference between this package and its sibling xpatch is that this package sports a very powerful \regexpatchcmd based on the l3regex module of the LaTeX3 experimental packages.

This package provides functions for making contour plots. The contour plot can be created from grid data, a function, or a data set. If non-grid data is given, then a Gaussian process is fit to the data and used to create the contour plot.

Facilitates the generation of input files for infraFDTD and processes snapshot output. infraFDTD is a finite-difference model written by Keehoon Kim for simulating infrasound that considers topography and a 1-D atmosphere (see Kim et al., 2015 <doi:10.1002/2015GL064466>).

Supervised classification methods, which (if asked) can provide step-by-step explanations of the algorithms used, as described in PK Josephine et. al., (2021) <doi:10.59176/kjcs.v1i1.1259>; and datasets to test them on, which highlight the strengths and weaknesses of each technique.

Change point tests for joint distributions and copulas using pseudo-observations with multipliers or bootstrap. The processes used here have been defined in Bucher, Kojadinovic, Rohmer & Segers <doi:10.1016/j.jmva.2014.07.012> and Nasri & Remillard <doi:10.1016/j.jmva.2019.03.002>.

This package provides a progress bar similar to dplyr that can write progress out to a variety of locations, including stdout(), stderr(), or from file(). Useful when using knitr or rmarkdown', and you still want to see progress of calculations in the terminal.