|
r-hashmap
|
public |
Provides a hash table class for fast key-value storage of atomic vector types.
|
2025-04-22 |
|
r-flare
|
public |
Provide the implementation of a family of Lasso variants including Dantzig Selector, LAD Lasso, SQRT Lasso, Lq Lasso for estimating high dimensional sparse linear model. We adopt the alternating direction method of multipliers and convert the original optimization problem into a sequential L1 penalized least square minimization problem, which can be efficiently solved by linearization algorithm. A multi-stage screening approach is adopted for further acceleration. Besides the sparse linear model estimation, we also provide the extension of these Lasso variants to sparse Gaussian graphical model estimation including TIGER and CLIME using either L1 or adaptive penalty. Missing values can be tolerated for Dantzig selector and CLIME. The computation is memory-optimized using the sparse matrix output.
|
2025-04-22 |
|
r-linkcomm
|
public |
Link communities reveal the nested and overlapping structure in networks, and uncover the key nodes that form connections to multiple communities. linkcomm provides a set of tools for generating, visualizing, and analysing link communities in networks of arbitrary size and type. The linkcomm package also includes tools for generating, visualizing, and analysing Overlapping Cluster Generator (OCG) communities.
|
2025-04-22 |
|
r-vbsr
|
public |
Efficient algorithm for solving ultra-sparse regularized regression models using a variational Bayes algorithm with a spike (l0) prior. Algorithm is solved on a path, with coordinate updates, and is capable of generating very sparse models. There are very general model diagnostics for controling type-1 error included in this package.
|
2025-04-22 |
|
r-mcl
|
public |
Contains the Markov cluster algorithm (MCL) for identifying clusters in networks and graphs. The algorithm simulates random walks on a (n x n) matrix as the adjacency matrix of a graph. It alternates an expansion step and an inflation step until an equilibrium state is reached.
|
2025-04-22 |
|
xorg-libxinerama
|
public |
Client library for the Xinerama extension to the X11 protocol.
|
2025-04-22 |
|
r-rinside
|
public |
C++ classes to embed R in C++ applications A C++ class providing the R interpreter is offered by this package making it easier to have "R inside" your C++ application. As R itself is embedded into your application, a shared library build of R is required. This works on Linux, OS X and even on Windows provided you use the same tools used to build R itself. d Numerous examples are provided in the eight subdirectories of the examples/ directory of the installed package: standard, 'mpi' (for parallel computing), 'qt' (showing how to embed 'RInside' inside a Qt GUI application), 'wt' (showing how to build a "web-application" using the Wt toolkit), 'armadillo' (for 'RInside' use with 'RcppArmadillo') and 'eigen' (for 'RInside' use with 'RcppEigen'). The examples use 'GNUmakefile(s)' with GNU extensions, so a GNU make is required (and will use the 'GNUmakefile' automatically). 'Doxygen'-generated documentation of the C++ classes is available at the 'RInside' website as well.
|
2025-04-22 |
|
lame
|
public |
High quality MPEG Audio Layer III (MP3) encoder
|
2025-04-22 |
|
xwebrtc
|
public |
C++ backend for the jupyter webrtc widget
|
2025-04-22 |
|
namaster
|
public |
pseudo-Cl power spectra w/ masking for spin-0 and spin-2 fields
|
2025-04-22 |
|
r-sparsebn
|
public |
Fast methods for learning sparse Bayesian networks from high-dimensional data using sparse regularization, as described in Aragam, Gu, and Zhou (2017) <arXiv:1703.04025>. Designed to handle mixed experimental and observational data with thousands of variables with either continuous or discrete observations.
|
2025-04-22 |
|
r-discretecdalgorithm
|
public |
Structure learning of Bayesian network using coordinate-descent algorithm. This algorithm is designed for discrete network assuming a multinomial data set, and we use a multi-logit model to do the regression. The algorithm is described in Gu, Fu and Zhou (2016) <arXiv:1403.2310>.
|
2025-04-22 |
|
r-fivethirtyeight
|
public |
Datasets and code published by the data journalism website 'FiveThirtyEight' available at <https://github.com/fivethirtyeight/data>. Note that while we received guidance from editors at 'FiveThirtyEight', this package is not officially published by 'FiveThirtyEight'.
|
2025-04-22 |
|
xleaflet
|
public |
C++ backend for the jupyter leaflet widget
|
2025-04-22 |
|
xplot
|
public |
C++ backend for the bqplot 2-D plotting library
|
2025-04-22 |
|
r-reordercluster
|
public |
Tools for performing the leaf reordering for the dendrogram that preserves the hierarchical clustering result and at the same time tries to group instances from the same class together.
|
2025-04-22 |
|
ghc
|
public |
Glorious Glasgow Haskell Compilation System
|
2025-04-22 |
|
r-fpp2
|
public |
All data sets required for the examples and exercises in the book "Forecasting: principles and practice" by Rob J Hyndman and George Athanasopoulos <https://OTexts.org/fpp2/>. All packages required to run the examples are also loaded.
|
2025-04-22 |
|
r-rtweet
|
public |
An implementation of calls designed to collect and organize Twitter data via Twitter's REST and stream Application Program Interfaces (API), which can be found at the following URL: <https://developer.twitter.com/en/docs>.
|
2025-04-22 |
|
r-textrecipes
|
public |
Converting text to numerical features requires specifically created procedures, which are implemented as steps according to the 'recipes' package. These steps allows for tokenization, filtering, counting (tf and tfidf) and feature hashing.
|
2025-04-22 |
|
ldas-tools-filters
|
public |
Filters library used by ldas-tools
|
2025-04-22 |
|
slang
|
public |
S-Lang allows developers to create robust multi-platform software
|
2025-04-22 |
|
r-lightgbm
|
public |
Tree based algorithms can be improved by introducing boosting frameworks. 'LightGBM' is one such framework, based on Ke, Guolin et al. (2017) <https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision>. This package offers an R interface to work with it. It is designed to be distributed and efficient with the following advantages: 1. Faster training speed and higher efficiency. 2. Lower memory usage. 3. Better accuracy. 4. Parallel learning supported. 5. Capable of handling large-scale data. In recognition of these advantages, 'LightGBM' has been widely-used in many winning solutions of machine learning competitions. Comparison experiments on public datasets suggest that 'LightGBM' can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. In addition, parallel experiments suggest that in certain circumstances, 'LightGBM' can achieve a linear speed-up in training time by using multiple machines.
|
2025-04-22 |
|
r-opencpu
|
public |
A system for embedded scientific computing and reproducible research with R. The OpenCPU server exposes a simple but powerful HTTP api for RPC and data interchange with R. This provides a reliable and scalable foundation for statistical services or building R web applications. The OpenCPU server runs either as a single-user development server within the interactive R session, or as a multi-user Linux stack based on Apache2. The entire system is fully open source and permissively licensed. The OpenCPU website has detailed documentation and example apps.
|
2025-04-22 |
|
r-hypergea
|
public |
Performs (exact) hypergeometric tests on IxJ and 2x2x2 contingency tables using parallelized C code.
|
2025-04-22 |
