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r-import
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public |
This is an alternative mechanism for importing objects from packages. The syntax allows for importing multiple objects from a package with a single command in an expressive way. The import package bridges some of the gap between using library (or require) and direct (single-object) imports. Furthermore the imported objects are not placed in the current environment. It is also possible to import objects from stand-alone .R files. For more information, refer to the package vignette.
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2025-04-22 |
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r-lassopv
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Estimate the p-values for predictors x against target variable y in lasso regression, using the regularization strength when each predictor enters the active set of regularization path for the first time as the statistic. This is based on the assumption that predictors (of the same variance) that (first) become active earlier tend to be more significant. Three null distributions are supported: normal and spherical, which are computed separately for each predictor and analytically under approximation, which aims at efficiency and accuracy for small p-values.
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2025-04-22 |
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r-verification
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Utilities for verifying discrete, continuous and probabilistic forecasts, and forecasts expressed as parametric distributions are included.
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2025-04-22 |
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r-mcl
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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.
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2025-04-22 |
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xorg-libxinerama
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public |
Client library for the Xinerama extension to the X11 protocol.
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2025-04-22 |
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r-rinside
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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.
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2025-04-22 |
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lame
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public |
High quality MPEG Audio Layer III (MP3) encoder
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2025-04-22 |
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xwebrtc
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public |
C++ backend for the jupyter webrtc widget
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2025-04-22 |
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r-pmcmrplus
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For one-way layout experiments the one-way ANOVA can be performed as an omnibus test. All-pairs multiple comparisons tests (Tukey-Kramer test, Scheffe test, LSD-test) and many-to-one tests (Dunnett test) for normally distributed residuals and equal within variance are available. Furthermore, all-pairs tests (Games-Howell test, Tamhane's T2 test, Dunnett T3 test, Ury-Wiggins-Hochberg test) and many-to-one (Tamhane-Dunnett Test) for normally distributed residuals and heterogeneous variances are provided. Van der Waerden's normal scores test for omnibus, all-pairs and many-to-one tests is provided for non-normally distributed residuals and homogeneous variances. The Kruskal-Wallis, BWS and Anderson-Darling omnibus test and all-pairs tests (Nemenyi test, Dunn test, Conover test, Dwass-Steele-Critchlow- Fligner test) as well as many-to-one (Nemenyi test, Dunn test, U-test) are given for the analysis of variance by ranks. Non-parametric trend tests (Jonckheere test, Cuzick test, Johnson-Mehrotra test, Spearman test) are included. In addition, a Friedman-test for one-way ANOVA with repeated measures on ranks (CRBD) and Skillings-Mack test for unbalanced CRBD is provided with consequent all-pairs tests (Nemenyi test, Siegel test, Miller test, Conover test, Exact test) and many-to-one tests (Nemenyi test, Demsar test, Exact test). A trend can be tested with Pages's test. Durbin's test for a two-way balanced incomplete block design (BIBD) is given in this package as well as Gore's test for CRBD with multiple observations per cell is given. Outlier tests, Mandel's k- and h statistic as well as functions for Type I error and Power analysis as well as generic summary, print and plot methods are provided.
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2025-04-22 |
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namaster
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public |
pseudo-Cl power spectra w/ masking for spin-0 and spin-2 fields
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2025-04-22 |
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r-sparsebn
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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.
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2025-04-22 |
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r-discretecdalgorithm
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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>.
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2025-04-22 |
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r-ccdralgorithm
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Implementation of the CCDr (Concave penalized Coordinate Descent with reparametrization) structure learning algorithm as described in Aragam and Zhou (2015) <http://www.jmlr.org/papers/v16/aragam15a.html>. This is a fast, score-based method for learning Bayesian networks that uses sparse regularization and block-cyclic coordinate descent.
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2025-04-22 |
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r-distr
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S4-classes and methods for distributions.
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2025-04-22 |
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r-fivethirtyeight
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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'.
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2025-04-22 |
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xleaflet
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public |
C++ backend for the jupyter leaflet widget
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2025-04-22 |
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xplot
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public |
C++ backend for the bqplot 2-D plotting library
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2025-04-22 |
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r-sparsebnutils
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A set of tools for representing and estimating sparse Bayesian networks from continuous and discrete data, as described in Aragam, Gu, and Zhou (2017) <arXiv:1703.04025>.
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2025-04-22 |
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r-teachingdemos
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public |
Demonstration functions that can be used in a classroom to demonstrate statistical concepts, or on your own to better understand the concepts or the programming.
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2025-04-22 |
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r-filematrix
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Interface for working with large matrices stored in files, not in computer memory. Supports multiple non-character data types (double, integer, logical and raw) of various sizes (e.g. 8 and 4 byte real values). Access to parts of the matrix is done by indexing, exactly as with usual R matrices. Supports very large matrices. Tested on multi-terabyte matrices. Allows for more than 2^32 rows or columns. Allows for quick addition of extra columns to a filematrix. Cross-platform as the package has R code only.
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2025-04-22 |
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r-reordercluster
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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.
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2025-04-22 |
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r-startupmsg
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Provides utilities to create or suppress start-up messages.
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2025-04-22 |
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ghc
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Glorious Glasgow Haskell Compilation System
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2025-04-22 |
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r-fpp2
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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.
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2025-04-22 |
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r-rosm
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Download and plot Open Street Map <http://www.openstreetmap.org/>, Bing Maps <http://www.bing.com/maps> and other tiled map sources. Use to create basemaps quickly and add hillshade to vector-based maps.
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2025-04-22 |
