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r-smacof
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public |
Implements the following approaches for multidimensional scaling (MDS) based on stress minimization using majorization (smacof): ratio/interval/ordinal/spline MDS on symmetric dissimilarity matrices, MDS with external constraints on the configuration, individual differences scaling (idioscal, indscal), MDS with spherical restrictions, and ratio/interval/ordinal/spline unfolding (circular restrictions, row-conditional). Various tools and extensions like jackknife MDS, bootstrap MDS, permutation tests, MDS biplots, gravity models, unidimensional scaling, drift vectors (asymmetric MDS), classical scaling, and Procrustes are implemented as well.
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2025-09-27 |
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r-mvoutlier
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public |
Various Methods for Multivariate Outlier Detection.
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2025-09-27 |
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pyabel
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public |
A Python package for forward and inverse Abel transforms
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2025-09-27 |
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zed
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public |
Code at the speed of thought
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2025-09-27 |
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r-plspm
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public |
Partial Least Squares Path Modeling (PLS-PM) analysis for both metric and non-metric data, as well as REBUS analysis.
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2025-09-27 |
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mlx
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public |
An array framework for Apple silicon
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2025-09-27 |
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r-rly
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public |
R implementation of the common parsing tools 'lex' and 'yacc'.
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2025-09-27 |
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r-raveio
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public |
Includes multiple cross-platform read/write interfaces for 'RAVE' project. 'RAVE'
stands for "R analysis and visualization of human intracranial electroencephalography
data". The whole project aims at providing powerful free-source package that analyze
brain recordings from patients with electrodes placed on the cortical surface or
inserted into the brain. 'raveio' as part of this project provides tools to read/write
neurophysiology data from/to 'RAVE' file structure, as well as several popular formats
including 'EDF(+)', 'Matlab', 'BIDS-iEEG', and 'HDF5', etc. Documentation and examples
about 'RAVE' project are provided at <https://openwetware.org/wiki/RAVE>, and the
paper by John F. Magnotti, Zhengjia Wang, Michael S. Beauchamp (2020) <doi:10.1016/j.neuroimage.2020.117341>;
see 'citation("raveio")' for details.
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2025-09-27 |
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r-robcompositions
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public |
Methods for analysis of compositional data including robust methods (<doi:10.1007/978-3-319-96422-5>), imputation of missing values (<doi:10.1016/j.csda.2009.11.023>), methods to replace rounded zeros (<doi:10.1080/02664763.2017.1410524>, <doi:10.1016/j.chemolab.2016.04.011>, <doi:10.1016/j.csda.2012.02.012>), count zeros (<doi:10.1177/1471082X14535524>), methods to deal with essential zeros (<doi:10.1080/02664763.2016.1182135>), (robust) outlier detection for compositional data, (robust) principal component analysis for compositional data, (robust) factor analysis for compositional data, (robust) discriminant analysis for compositional data (Fisher rule), robust regression with compositional predictors, functional data analysis and p-splines (<doi:10.1016/j.csda.2015.07.007>), contingency (<doi:10.1080/03610926.2013.824980>) and compositional tables (<doi:10.1111/sjos.12326>, <doi:10.1111/sjos.12223>, <doi:10.1080/02664763.2013.856871>) and (robust) Anderson-Darling normality tests for compositional data as well as popular log-ratio transformations (addLR, cenLR, isomLR, and their inverse transformations). In addition, visualisation and diagnostic tools are implemented as well as high and low-level plot functions for the ternary diagram.
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2025-09-27 |
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r-rselenium
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public |
Provides a set of R bindings for the 'Selenium 2.0 WebDriver' (see <https://selenium.dev/documentation/en/> for more information) using the 'JsonWireProtocol' (see <https://github.com/SeleniumHQ/selenium/wiki/JsonWireProtocol> for more information). 'Selenium 2.0 WebDriver' allows driving a web browser natively as a user would either locally or on a remote machine using the Selenium server it marks a leap forward in terms of web browser automation. Selenium automates web browsers (commonly referred to as browsers). Using RSelenium you can automate browsers locally or remotely.
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2025-09-27 |
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mp-api
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public |
API Client for the Materials Project
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2025-09-27 |
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r-rio
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public |
Streamlined data import and export by making assumptions that the user is probably willing to make: 'import()' and 'export()' determine the data structure from the file extension, reasonable defaults are used for data import and export (e.g., 'stringsAsFactors=FALSE'), web-based import is natively supported (including from SSL/HTTPS), compressed files can be read directly without explicit decompression, and fast import packages are used where appropriate. An additional convenience function, 'convert()', provides a simple method for converting between file types.
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2025-09-27 |
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r-climate4r.value
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public |
Wrapper of package VALUE to compute several indices and perform climate data validation using the tools developed in the COST action VALUE <http://www.value-cost.eu/>.
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2025-09-27 |
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boto3
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public |
Amazon Web Services SDK for Python
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2025-09-27 |
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overturemaps
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public |
Python tools for interacting with Overture Maps (overturemaps.org) data.
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2025-09-27 |
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r-candisc
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public |
Functions for computing and visualizing generalized canonical discriminant analyses and canonical correlation analysis for a multivariate linear model. Traditional canonical discriminant analysis is restricted to a one-way 'MANOVA' design and is equivalent to canonical correlation analysis between a set of quantitative response variables and a set of dummy variables coded from the factor variable. The 'candisc' package generalizes this to higher-way 'MANOVA' designs for all factors in a multivariate linear model, computing canonical scores and vectors for each term. The graphic functions provide low-rank (1D, 2D, 3D) visualizations of terms in an 'mlm' via the 'plot.candisc' and 'heplot.candisc' methods. Related plots are now provided for canonical correlation analysis when all predictors are quantitative.
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2025-09-27 |
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r-ryacas
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public |
Interface to the 'yacas' computer algebra system (<http://www.yacas.org/>).
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2025-09-27 |
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r-qpcr
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public |
Model fitting, optimal model selection and calculation of various features that are essential in the analysis of quantitative real-time polymerase chain reaction (qPCR).
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2025-09-27 |
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ssm-simulators
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public |
SSMS is a package collecting simulators and training data generators for a bunch of generative models of interest in the cognitive science / neuroscience and approximate bayesian computation communities
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2025-09-27 |
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r-kmlshape
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public |
K-means for longitudinal data using shape-respecting distance and shape-respecting means.
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2025-09-26 |
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trimesh
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public |
Import, export, process, analyze and view triangular meshes.
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2025-09-26 |
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gradio-client
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public |
Python library for easily interacting with trained machine learning models
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2025-09-26 |
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google-genai
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public |
GenAI Python SDK
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2025-09-26 |
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r-tsdist
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public |
A set of commonly used distance measures and some additional functions which, although initially not designed for this purpose, can be used to measure the dissimilarity between time series. These measures can be used to perform clustering, classification or other data mining tasks which require the definition of a distance measure between time series.
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2025-09-26 |
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zizmor
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public |
Static analysis for GitHub Actions
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2025-09-26 |
