# Yixuan Qiu

#### 21 packages on CRAN

Creating tiny yet beautiful documents and vignettes from R Markdown. The package provides the 'html_pretty' output format as an alternative to the 'html_document' and 'html_vignette' engines that convert R Markdown into HTML pages. Various themes and syntax highlight styles are supported.

Using the 'Ming' library <http://www.libming.org/> to create Flash animations. Users can either use the 'SWF' device swf() to generate 'SWF' file directly through plotting functions like plot() and lines(), or convert images of other formats ('SVG', 'PNG', 'JPEG') into 'SWF'.

Previously an R wrapper of the 'ARPACK' library <http://www.caam.rice.edu/software/ARPACK/>, and now a shell of the R package 'RSpectra', an R interface to the 'Spectra' library <http://yixuan.cos.name/spectra/> for solving large scale eigenvalue/vector problems. The current version of 'rARPACK' simply imports and exports the functions provided by 'RSpectra'. New users of 'rARPACK' are advised to switch to the 'RSpectra' package.

This package provides several functions to manipulate rational functions, including basic arithmetic operators, derivatives and integrals with EXPLICIT forms.

A collection of open source libraries for numerical computing (numerical integration, optimization, etc.) and their integration with 'Rcpp'.

R wrapper of the 'libmf' library <http://www.csie.ntu.edu.tw/~cjlin/libmf/> for recommender system using matrix factorization. It is typically used to approximate an incomplete matrix using the product of two matrices in a latent space. Other common names for this task include "collaborative filtering", "matrix completion", "matrix recovery", etc. High performance multi-core parallel computing is supported in this package.

R interface to the 'Spectra' library <https://spectralib.org/> for large-scale eigenvalue and SVD problems. It is typically used to compute a few eigenvalues/vectors of an n by n matrix, e.g., the k largest eigenvalues, which is usually more efficient than eigen() if k << n. This package provides the 'eigs()' function that does the similar job as in 'Matlab', 'Octave', 'Python SciPy' and 'Julia'. It also provides the 'svds()' function to calculate the largest k singular values and corresponding singular vectors of a real matrix. The matrix to be computed on can be dense, sparse, or in the form of an operator defined by the user.

Making it easy to use various types of fonts ('TrueType', 'OpenType', Type 1, web fonts, etc.) in R graphs, and supporting most output formats of R graphics including PNG, PDF and SVG. Text glyphs will be converted into polygons or raster images, hence after the plot has been created, it no longer relies on the font files. No external software such as 'Ghostscript' is needed to use this package.

Loading system fonts and Google Fonts <https://fonts.google.com/> into R, in order to support other packages such as 'R2SWF' and 'showtext'.

Output formats and utilities for authoring books and technical documents with R Markdown.

Fits generalized linear models efficiently using 'RcppEigen'. The iteratively reweighted least squares implementation utilizes the step-halving approach of Marschner (2011) <doi:10.32614/RJ-2011-012> to help safeguard against convergence issues.

This is a collection of R games and other funny stuff, such as the classic Mine sweeper and sliding puzzles.

Provides syntax highlighting for R source code. Currently it supports LaTeX and HTML output. Source code of other languages is supported via Andre Simon's highlight package (<http://www.andre-simon.de>).

Provides R bindings to the 'Sundown' Markdown rendering library (<https://github.com/vmg/sundown>). Markdown is a plain-text formatting syntax that can be converted to 'XHTML' or other formats. See <http://en.wikipedia.org/wiki/Markdown> for more information about Markdown.

Solves penalized least squares problems for big tall data using the orthogonalizing EM algorithm of Xiong et al. (2016) <doi:10.1080/00401706.2015.1054436>. The main fitting function is oem() and the functions cv.oem() and xval.oem() are for cross validation, the latter being an accelerated cross validation function for linear models. The big.oem() function allows for out of memory fitting.

R and 'Eigen' integration using 'Rcpp'. 'Eigen' is a C++ template library for linear algebra: matrices, vectors, numerical solvers and related algorithms. It supports dense and sparse matrices on integer, floating point and complex numbers, decompositions of such matrices, and solutions of linear systems. Its performance on many algorithms is comparable with some of the best implementations based on 'Lapack' and level-3 'BLAS'. The 'RcppEigen' package includes the header files from the 'Eigen' C++ template library (currently version 3.3.4). Thus users do not need to install 'Eigen' itself in order to use 'RcppEigen'. Since version 3.1.1, 'Eigen' is licensed under the Mozilla Public License (version 2); earlier version were licensed under the GNU LGPL version 3 or later. 'RcppEigen' (the 'Rcpp' bindings/bridge to 'Eigen') is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'.

A graphics device for R that produces 'Scalable Vector Graphics'. 'svglite' is a fork of the older 'RSvgDevice' package.

An extension to the 'testthat' package that makes it easy to add graphical unit tests. It provides a Shiny application to manage the test cases.

Provides variable selection and estimation routines for models with main effects stratified on multiple binary factors. The 'vennLasso' package is an implementation of the method introduced in Huling, et al. (2017) <doi:10.1111/biom.12769>.