libminc
|
public |
libminc standalone
|
2024-09-19 |
minc-toolkit-v2
|
public |
Toolkit for processing MRI scans (external libraries)
|
2023-08-21 |
nano
|
public |
Nano's ANOther editor, an enhanced free Pico clone
|
2023-06-16 |
r-doparallel
|
public |
Provides a parallel backend for the %dopar% function using the parallel package.
|
2023-06-16 |
r-foreach
|
public |
Support for the foreach looping construct. Foreach is an idiom that allows for iterating over elements in a collection, without the use of an explicit loop counter. This package in particular is intended to be used for its return value, rather than for its side effects. In that sense, it is similar to the standard lapply function, but doesn't require the evaluation of a function. Using foreach without side effects also facilitates executing the loop in parallel.
|
2023-06-16 |
r-r6
|
public |
Creates classes with reference semantics, similar to R's built-in reference classes. Compared to reference classes, R6 classes are simpler and lighter-weight, and they are not built on S4 classes so they do not require the methods package. These classes allow public and private members, and they support inheritance, even when the classes are defined in different packages.
|
2023-06-16 |
qrencode
|
public |
QR code generator
|
2023-06-16 |
r-ellipsis
|
public |
The ellipsis is a powerful tool for extending functions. Unfortunately this power comes at a cost: misspelled arguments will be silently ignored. The ellipsis package provides a collection of functions to catch problems and alert the user.
|
2023-06-16 |
r-rlang
|
public |
A toolbox for working with base types, core R features like the condition system, and core 'Tidyverse' features like tidy evaluation.
|
2023-06-16 |
r-cpp11
|
public |
Provides a header only, C++11 interface to R's C interface. Compared to other approaches 'cpp11' strives to be safe against long jumps from the C API as well as C++ exceptions, conform to normal R function semantics and supports interaction with 'ALTREP' vectors.
|
2023-06-16 |
r-vctrs
|
public |
Defines new notions of prototype and size that are used to provide tools for consistent and well-founded type-coercion and size-recycling, and are in turn connected to ideas of type- and size-stability useful for analysing function interfaces.
|
2023-06-16 |
arrow-cpp
|
public |
C++ libraries for Apache Arrow
|
2023-06-16 |
r-arrow
|
public |
R Integration to 'Apache' 'Arrow'.
|
2023-06-16 |
lifelines
|
public |
Survival analysis in Python, including Kaplan Meier, Nelson Aalen and regression
|
2023-06-16 |
autograd-gamma
|
public |
Autograd compatible approximations to the gamma family of functions
|
2023-06-16 |
autograd
|
public |
Efficiently computes derivatives of numpy code.
|
2023-06-16 |
nilearn
|
public |
Statistical learning for neuroimaging in Python
|
2023-06-16 |
medpy
|
public |
Medical image processing in Python
|
2023-06-16 |
r-bigstatsr
|
public |
Easy-to-use, efficient, flexible and scalable statistical tools. Package bigstatsr provides and uses Filebacked Big Matrices via memory-mapping. It provides for instance matrix operations, Principal Component Analysis, sparse linear supervised models, utility functions and more <doi:10.1093/bioinformatics/bty185>.
|
2023-06-16 |
r-rmio
|
public |
Provides header files of 'mio', a cross-platform C++11 header-only library for memory mapped file IO <https://github.com/mandreyel/mio>.
|
2023-06-16 |
r-bigparallelr
|
public |
Utility functions for easy parallelism in R. Include some reexports from other packages, utility functions for splitting and parallelizing over blocks, and choosing and setting the number of cores used.
|
2023-06-16 |
r-bigassertr
|
public |
Enhanced message functions (cat() / message() / warning() / error()) using wrappers around sprintf(). Also, multiple assertion functions (e.g. to check class, length, values, files, arguments, etc.).
|
2023-06-16 |
r-rspectra
|
public |
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.
|
2023-06-16 |
falcon
|
public |
Falcon cortical thickness measurement
|
2023-06-16 |
minc2-simple
|
public |
Python library for MINC IO, using minc2 API and CFFI
|
2023-06-16 |
yq
|
public |
Command-line YAML/XML processor - jq wrapper for YAML/XML documents
|
2023-06-16 |
r-mlr
|
public |
Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensitive learning. Generic resampling, including cross-validation, bootstrapping and subsampling. Hyperparameter tuning with modern optimization techniques, for single- and multi-objective problems. Filter and wrapper methods for feature selection. Extension of basic learners with additional operations common in machine learning, also allowing for easy nested resampling. Most operations can be parallelized.
|
2023-06-16 |
r-data.table
|
public |
Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns, friendly and fast character-separated-value read/write. Offers a natural and flexible syntax, for faster development.
|
2023-06-16 |
r-paramhelpers
|
public |
Functions for parameter descriptions and operations in black-box optimization, tuning and machine learning. Parameters can be described (type, constraints, defaults, etc.), combined to parameter sets and can in general be programmed on. A useful OptPath object (archive) to log function evaluations is also provided.
|
2023-06-16 |
r-flexdashboard
|
public |
Format for converting an R Markdown document to a grid oriented dashboard. The dashboard flexibly adapts the size of it's components to the containing web page.
|
2023-06-16 |
r-classint
|
public |
Selected commonly used methods for choosing univariate class intervals for mapping or other graphics purposes.
|
2023-06-16 |
mrtrix3
|
public |
No Summary
|
2023-06-16 |
sed
|
public |
sed (stream editor) is a non-interactive command-line text editor.
|
2023-06-16 |
octave
|
public |
GNU Octave is a high-level language, primarily intended for numerical computations
|
2023-06-16 |
arpack
|
public |
Fortran77 subroutines designed to solve large scale eigenvalue problems
|
2023-06-16 |
qhull
|
public |
Qhull computes the convex hull
|
2023-06-16 |
r-plotrix
|
public |
Lots of plots, various labeling, axis and color scaling functions.
|
2023-06-16 |
pycocotools
|
public |
Library to work with COCO dataset.
|
2023-06-16 |
r-rptr
|
public |
Estimating repeatability (intra-class correlation) from Gaussian, binary, proportion and Poisson data.
|
2023-06-16 |
gnuplot-nox11
|
public |
Gnuplot, plotting from command line
|
2023-06-16 |
r-pbapply
|
public |
A lightweight package that adds progress bar to vectorized R functions ('*apply'). The implementation can easily be added to functions where showing the progress is useful (e.g. bootstrap). The type and style of the progress bar (with percentages or remaining time) can be set through options. Supports several parallel processing backends.
|
2023-06-16 |
r-ucminf
|
public |
An algorithm for general-purpose unconstrained non-linear optimization. The algorithm is of quasi-Newton type with BFGS updating of the inverse Hessian and soft line search with a trust region type monitoring of the input to the line search algorithm. The interface of 'ucminf' is designed for easy interchange with 'optim'.
|
2023-06-16 |
r-mlbench
|
public |
A collection of artificial and real-world machine learning benchmark problems, including, e.g., several data sets from the UCI repository.
|
2023-06-16 |
r-mitml
|
public |
Provides tools for multiple imputation of missing data in multilevel modeling. Includes a user-friendly interface to the packages 'pan' and 'jomo', and several functions for visualization, data management and the analysis of multiply imputed data sets.
|
2023-06-16 |
r-ordinal
|
public |
Implementation of cumulative link (mixed) models also known as ordered regression models, proportional odds models, proportional hazards models for grouped survival times and ordered logit/probit/... models. Estimation is via maximum likelihood and mixed models are fitted with the Laplace approximation and adaptive Gauss-Hermite quadrature. Multiple random effect terms are allowed and they may be nested, crossed or partially nested/crossed. Restrictions of symmetry and equidistance can be imposed on the thresholds (cut-points/intercepts). Standard model methods are available (summary, anova, drop-methods, step, confint, predict etc.) in addition to profile methods and slice methods for visualizing the likelihood function and checking convergence.
|
2023-06-16 |
r-mice
|
public |
Multiple imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm as described in Van Buuren and Groothuis-Oudshoorn (2011) <doi:10.18637/jss.v045.i03>. Each variable has its own imputation model. Built-in imputation models are provided for continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data (proportional odds). MICE can also impute continuous two-level data (normal model, pan, second-level variables). Passive imputation can be used to maintain consistency between variables. Various diagnostic plots are available to inspect the quality of the imputations.
|
2023-06-16 |
r-kernlab
|
public |
Kernel-based machine learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Among other methods 'kernlab' includes Support Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes and a QP solver.
|
2023-06-16 |
r-jomo
|
public |
Similarly to Schafer's package 'pan', 'jomo' is a package for multilevel joint modelling multiple imputation (Carpenter and Kenward, 2013) <doi: 10.1002/9781119942283>. Novel aspects of 'jomo' are the possibility of handling binary and categorical data through latent normal variables, the option to use cluster-specific covariance matrices and to impute compatibly with the substantive model.
|
2023-06-16 |
r-pan
|
public |
It provides functions and examples for maximum likelihood estimation for generalized linear mixed models and Gibbs sampler for multivariate linear mixed models with incomplete data, as described in Schafer JL (1997) "Imputation of missing covariates under a multivariate linear mixed model". Technical report 97-04, Dept. of Statistics, The Pennsylvania State University.
|
2023-06-16 |
r-ggally
|
public |
The R package 'ggplot2' is a plotting system based on the grammar of graphics. 'GGally' extends 'ggplot2' by adding several functions to reduce the complexity of combining geometric objects with transformed data. Some of these functions include a pairwise plot matrix, a two group pairwise plot matrix, a parallel coordinates plot, a survival plot, and several functions to plot networks.
|
2023-06-16 |