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Package Name Access Summary Updated
ray-observability public Ray is a fast and simple framework for building and running distributed applications. 2025-09-29
ray-train public Ray is a fast and simple framework for building and running distributed applications. 2025-09-29
ray-default public Ray is a fast and simple framework for building and running distributed applications. 2025-09-29
ray-rllib public Ray is a fast and simple framework for building and running distributed applications. 2025-09-29
ray-air public Ray is a fast and simple framework for building and running distributed applications. 2025-09-29
ray-all public Ray is a fast and simple framework for building and running distributed applications. 2025-09-29
r-mashr public Implements the multivariate adaptive shrinkage (mash) method of Urbut et al (2019) <DOI:10.1038/s41588-018-0268-8> for estimating and testing large numbers of effects in many conditions (or many outcomes). Mash takes an empirical Bayes approach to testing and effect estimation; it estimates patterns of similarity among conditions, then exploits these patterns to improve accuracy of the effect estimates. The core linear algebra is implemented in C++ for fast model fitting and posterior computation. 2025-09-29
lazyslide public Modularized and scalable whole slide image analysis 2025-09-29
r-wordspace public An interactive laboratory for research on distributional semantic models ('DSM', see <https://en.wikipedia.org/wiki/Distributional_semantics> for more information). 2025-09-28
ray-adag public Ray is a fast and simple framework for building and running distributed applications. 2025-09-28
ray-cgraph public Ray is a fast and simple framework for building and running distributed applications. 2025-09-28
selectolax public Fast HTML5 parser with CSS selectors. 2025-09-28
go-sops public sops manages JSON, YAML and BINARY documents to be encrypted or decrypted. 2025-09-28
libsixel public SIXEL encoder/decoder implementation 2025-09-28
hoomd public HOOMD-blue is a general-purpose particle simulation toolkit. 2025-09-28
pymatgen-io-validation public A comprehensive I/O validator for electronic structure calculations 2025-09-28
r-gsignal public R implementation of the 'Octave' package 'signal', containing a variety of signal processing tools, such as signal generation and measurement, correlation and convolution, filtering, filter design, filter analysis and conversion, power spectrum analysis, system identification, decimation and sample rate change, and windowing. 2025-09-28
r-spatialpack public Tools to assess the association between two spatial processes. Currently, several methodologies are implemented: A modified t-test to perform hypothesis testing about the independence between the processes, a suitable nonparametric correlation coefficient, the codispersion coefficient, and an F test for assessing the multiple correlation between one spatial process and several others. Functions for image processing and computing the spatial association between images are also provided. SpatialPack gives methods to complement methodologies that are available in geoR for one spatial process. 2025-09-28
r-rpact public Design and analysis of confirmatory adaptive clinical trials with continuous, binary, and survival endpoints according to the methods described in the monograph by Wassmer and Brannath (2016) <doi:10.1007/978-3-319-32562-0>. This includes classical group sequential as well as multi-stage adaptive hypotheses tests that are based on the combination testing principle. 2025-09-28
r-bas public Package for Bayesian Variable Selection and Model Averaging in linear models and generalized linear models using stochastic or deterministic sampling without replacement from posterior distributions. Prior distributions on coefficients are from Zellner's g-prior or mixtures of g-priors corresponding to the Zellner-Siow Cauchy Priors or the mixture of g-priors from Liang et al (2008) <DOI:10.1198/016214507000001337> for linear models or mixtures of g-priors from Li and Clyde (2019) <DOI:10.1080/01621459.2018.1469992> in generalized linear models. Other model selection criteria include AIC, BIC and Empirical Bayes estimates of g. Sampling probabilities may be updated based on the sampled models using sampling w/out replacement or an efficient MCMC algorithm which samples models using a tree structure of the model space as an efficient hash table. See Clyde, Ghosh and Littman (2010) <DOI:10.1198/jcgs.2010.09049> for details on the sampling algorithms. Uniform priors over all models or beta-binomial prior distributions on model size are allowed, and for large p truncated priors on the model space may be used to enforce sampling models that are full rank. The user may force variables to always be included in addition to imposing constraints that higher order interactions are included only if their parents are included in the model. This material is based upon work supported by the National Science Foundation under Division of Mathematical Sciences grant 1106891. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. 2025-09-28
r-sparsesvd public Wrapper around the 'SVDLIBC' library for (truncated) singular value decomposition of a sparse matrix. Currently, only sparse real matrices in Matrix package format are supported. 2025-09-28
r-geor public Geostatistical analysis including variogram-based, likelihood-based and Bayesian methods. Software companion for Diggle and Ribeiro (2007) <doi:10.1007/978-0-387-48536-2>. 2025-09-28
xtensor-r public R bindings for xtensor, the C++ tensor algebra library 2025-09-28
r-refund public Methods for regression for functional data, including function-on-scalar, scalar-on-function, and function-on-function regression. Some of the functions are applicable to image data. 2025-09-28
polycap public Polycapillary X-ray raytracing 2025-09-28

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