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Enter the query into the form above. You can look for specific version of a package by using @ symbol like this: gcc@10.

API method:

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If you'd like to join our channel search send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.


r-bitmexr 0.3.3
Propagated dependencies: r-stringr@1.6.0 r-rlang@1.2.0 r-purrr@1.2.2 r-progress@1.2.3 r-magrittr@2.0.5 r-lubridate@1.9.5 r-jsonlite@2.0.0 r-httr@1.4.8 r-dplyr@1.2.1 r-digest@0.6.39 r-curl@7.1.0 r-attempt@0.3.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/hfshr/bitmexr/
Licenses: Expat
Build system: r
Synopsis: R Client for BitMEX
Description:

This package provides a client for cryptocurrency exchange BitMEX <https://www.bitmex.com/> including the ability to obtain historic trade data and place, edit and cancel orders. BitMEX's Testnet and live API are both supported.

r-bamm 0.6.2
Dependencies: sqlite@3.39.3 geos@3.12.1
Propagated dependencies: r-sp@2.2-1 r-rspectra@0.16-2 r-rdpack@2.6.6 r-rcpparmadillo@15.2.6-1 r-rcpp@1.1.1-1.1 r-raster@3.6-32 r-purrr@1.2.2 r-matrix@1.7-5 r-magrittr@2.0.5 r-leaflet@2.2.3 r-igraph@2.3.1 r-future@1.70.0 r-furrr@0.4.0 r-dplyr@1.2.1 r-animation@2.8
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://luismurao.github.io/bamm/
Licenses: GPL 3+
Build system: r
Synopsis: Species Distribution Models as a Function of Biotic, Abiotic and Movement Factors (BAM)
Description:

Species Distribution Modeling (SDM) is a practical methodology that aims to estimate the area of distribution of a species. However, most of the work has focused on estimating static expressions of the correlation between environmental variables. The outputs of correlative species distribution models can be interpreted as maps of the suitable environment for a species but not generally as maps of its actual distribution. Soberón and Peterson (2005) <doi:10.17161/bi.v2i0.4> presented the BAM scheme, a heuristic framework that states that the occupied area of a species occurs on sites that have been accessible through dispersal (M) and have both favorable biotic (B) and abiotic conditions (A). The bamm package implements classes and functions to operate on each element of the BAM and by using a cellular automata model where the occupied area of a species at time t is estimated by the multiplication of three binary matrices: one matrix represents movements (M), another abiotic -niche- tolerances (A), and a third, biotic interactions (B). The theoretical background of the package can be found in Soberón and Osorio-Olvera (2023) <doi:10.1111/jbi.14587>.

r-bundesbank 0.1-12
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: http://enricoschumann.net/R/packages/bundesbank/index.htm
Licenses: GPL 3
Build system: r
Synopsis: Download Data from Bundesbank
Description:

Download data from the time-series databases of the Bundesbank, the German central bank. See the overview at the Bundesbank website (<https://www.bundesbank.de/en/statistics/time-series-databases>) for available series. The package provides only a single function, getSeries(), which supports both traditional and real-time datasets; it will also download meta data if available. Downloaded data can automatically be arranged in various formats, such as data frames or zoo series. The data may optionally be cached, so as to avoid repeated downloads of the same series.

r-binnonnor 1.5.3
Propagated dependencies: r-mvtnorm@1.3-7 r-matrix@1.7-5 r-corpcor@1.6.10 r-bb@2026.1.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BinNonNor
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Data Generation with Binary and Continuous Non-Normal Components
Description:

Generation of multiple binary and continuous non-normal variables simultaneously given the marginal characteristics and association structure based on the methodology proposed by Demirtas et al. (2012) <DOI:10.1002/sim.5362>.

r-bodycompref 2.0.2
Propagated dependencies: r-sae@1.3 r-gamlss@5.5-0 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://bodycomp-metrics.mgh.harvard.edu
Licenses: GPL 3+
Build system: r
Synopsis: Reference Values for CT-Assessed Body Composition
Description:

Get z-scores, percentiles, absolute values, and percent of predicted of a reference cohort. Functionality requires installing the data packages adiposerefdata and musclerefdata from p-mq.github.io/drat. For more information on the underlying research, please visit our website which also includes a graphical interface. The models and underlying data are described in Marquardt J. Peter et al (2025), "Subcutaneous and Visceral adipose tissue Reference Values from Framingham Heart Study Thoracic and Abdominal CT", *Investigative Radiology* <doi:10.1097/RLI.0000000000001104> and Tonnesen PE et al. (2023), "Muscle Reference Values from Thoracic and Abdominal CT for Sarcopenia Assessment [column] The Framingham Heart Study", *Investigative Radiology*, <doi:10.1097/RLI.0000000000001012>.

r-basinetentropy 0.99.6
Propagated dependencies: r-randomforest@4.7-1.2 r-igraph@2.3.1 r-biostrings@2.80.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BASiNETEntropy
Licenses: GPL 3
Build system: r
Synopsis: Classification of RNA Sequences using Complex Network and Information Theory
Description:

It makes the creation of networks from sequences of RNA, with this is done the abstraction of characteristics of these networks with a methodology of maximum entropy for the purpose of making a classification between the classes of the sequences. There are two data present in the BASiNET package, "mRNA", and "ncRNA" with 10 sequences. These sequences were taken from the data set used in the article (LI, Aimin; ZHANG, Junying; ZHOU, Zhongyin, 2014) <doi:10.1186/1471-2105-15-311>, these sequences are used to run examples.

r-bulkqc 1.1
Propagated dependencies: r-stddiff@3.1 r-isotree@0.6.1-5
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bulkQC
Licenses: GPL 3
Build system: r
Synopsis: Quality Control and Outlier Identification in Bulk for Multicenter Trials
Description:

Multicenter randomized trials involve the collection and analysis of data from numerous study participants across multiple sites. Outliers may be present. To identify outliers, this package examines data at the individual level (univariate and multivariate) and site-level (with and without covariate adjustment). Methods are outlined in further detail in Rigdon et al (to appear).

r-bayesian 1.0.1
Propagated dependencies: r-tibble@3.3.1 r-rlang@1.2.0 r-purrr@1.2.2 r-parsnip@1.6.0 r-dplyr@1.2.1 r-brms@2.23.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://hsbadr.github.io/bayesian/
Licenses: Expat
Build system: r
Synopsis: Bindings for Bayesian TidyModels
Description:

Fit Bayesian models using brms'/'Stan with parsnip'/'tidymodels via bayesian <doi:10.5281/zenodo.4426836>. tidymodels is a collection of packages for machine learning; see Kuhn and Wickham (2020) <https://www.tidymodels.org>). The technical details of brms and Stan are described in Bürkner (2017) <doi:10.18637/jss.v080.i01>, Bürkner (2018) <doi:10.32614/RJ-2018-017>, and Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.

r-bacondecomp 0.1.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bacondecomp
Licenses: Expat
Build system: r
Synopsis: Goodman-Bacon Decomposition
Description:

Decomposition for differences-in-differences with variation in treatment timing from Goodman-Bacon (2018) <doi:10.3386/w25018>.

r-bmemlavaan 0.7
Propagated dependencies: r-snowfall@1.84-6.3 r-sem@3.1-16 r-rsem@0.5.1 r-mass@7.3-65 r-lavaan@0.6-21 r-amelia@1.8.3
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://bigdatalab.nd.edu
Licenses: GPL 2
Build system: r
Synopsis: Mediation Analysis with Missing Data and Non-Normal Data
Description:

This package provides methods for mediation analysis with missing data and non-normal data are implemented. For missing data, four methods are available: Listwise deletion, Pairwise deletion, Multiple imputation, and Two Stage Maximum Likelihood algorithm. For MI and TS-ML, auxiliary variables can be included to handle missing data. For handling non-normal data, bootstrap and two-stage robust methods can be used. Technical details of the methods can be found in Zhang and Wang (2013, <doi:10.1007/s11336-012-9301-5>), Zhang (2014, <doi:10.3758/s13428-013-0424-0>), and Yuan and Zhang (2012, <doi:10.1007/s11336-012-9282-4>).

r-breadr 1.1.0
Propagated dependencies: r-tidyr@1.3.2 r-tibble@3.3.1 r-stringr@1.6.0 r-readr@2.2.0 r-purrr@1.2.2 r-matrixstats@1.5.0 r-mass@7.3-65 r-magrittr@2.0.5 r-ggstatsplot@1.0.0 r-ggpubr@0.6.3 r-ggplot2@4.0.3 r-forcats@1.0.1 r-dplyr@1.2.1 r-data-table@1.18.4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/jonotuke/BREADR
Licenses: Expat
Build system: r
Synopsis: Estimates Degrees of Relatedness (Up to the Second Degree) for Extreme Low-Coverage Data
Description:

The goal of the package is to provide an easy-to-use method for estimating degrees of relatedness (up to the second degree) for extreme low-coverage data. The package also allows users to quantify and visualise the level of confidence in the estimated degrees of relatedness.

r-bfs 0.7.2
Propagated dependencies: r-zip@2.3.3 r-xml2@1.5.2 r-tidyr@1.3.2 r-tibble@3.3.1 r-rvest@1.0.5 r-rlang@1.2.0 r-pxweb@0.19.2 r-purrr@1.2.2 r-magrittr@2.0.5 r-lifecycle@1.0.5 r-janitor@2.2.1 r-httr2@1.2.2 r-fs@2.1.0 r-dplyr@1.2.1 r-curl@7.1.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://felixluginbuhl.com/BFS/
Licenses: GPL 3+
Build system: r
Synopsis: Get Data from the Swiss Federal Statistical Office
Description:

Search and download data from the Swiss Federal Statistical Office (BFS) APIs <https://www.bfs.admin.ch/>.

r-bspm 0.5.8
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran4linux.github.io/bspm/
Licenses: Expat
Build system: r
Synopsis: Bridge to System Package Manager
Description:

Enables binary package installations on Linux distributions. Provides functions to manage packages via the distribution's package manager. Also provides transparent integration with R's install.packages() and a fallback mechanism. When installed as a system package, interacts with the system's package manager without requiring administrative privileges via an integrated D-Bus service; otherwise, uses sudo. Currently, the following backends are supported: DNF, APT, ALPM.

r-biopixr 1.2.0
Propagated dependencies: r-magick@2.9.1 r-imager@1.0.8 r-data-table@1.18.4 r-cluster@2.1.8.2
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/Brauckhoff/biopixR
Licenses: LGPL 3+
Build system: r
Synopsis: Extracting Insights from Biological Images
Description:

Combines the magick and imager packages to streamline image analysis, focusing on feature extraction and quantification from biological images, especially microparticles. By providing high throughput pipelines and clustering capabilities, biopixR facilitates efficient insight generation for researchers (Schneider J. et al. (2019) <doi:10.21037/jlpm.2019.04.05>).

r-bikm1 1.1.0
Propagated dependencies: r-reshape2@1.4.5 r-pracma@2.4.6 r-lpsolve@5.6.23 r-gtools@3.9.5 r-ggplot2@4.0.3 r-ade4@1.7-24
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bikm1
Licenses: GPL 2
Build system: r
Synopsis: Co-Clustering Adjusted Rand Index and Bikm1 Procedure for Contingency and Binary Data-Sets
Description:

Co-clustering of the rows and columns of a contingency or binary matrix, or double binary matrices and model selection for the number of row and column clusters. Three models are considered: the Poisson latent block model for contingency matrix, the binary latent block model for binary matrix and a new model we develop: the multiple latent block model for double binary matrices. A new procedure named bikm1 is implemented to investigate more efficiently the grid of numbers of clusters. Then, the studied model selection criteria are the integrated completed likelihood (ICL) and the Bayesian integrated likelihood (BIC). Finally, the co-clustering adjusted Rand index (CARI) to measure agreement between co-clustering partitions is implemented. Robert Valerie, Vasseur Yann, Brault Vincent (2021) <doi:10.1007/s00357-020-09379-w>.

r-boxplotcluster 0.3
Propagated dependencies: r-cluster@2.1.8.2
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=boxplotcluster
Licenses: GPL 2+
Build system: r
Synopsis: Clustering Method Based on Boxplot Statistics
Description:

Following Arroyo-Maté-Roque (2006), the function calculates the distance between rows or columns of the dataset using the generalized Minkowski metric as described by Ichino-Yaguchi (1994). The distance measure gives more weight to differences between quartiles than to differences between extremes, making it less sensitive to outliers. Further,the function calculates the silhouette width (Rousseeuw 1987) for different numbers of clusters and selects the number of clusters that maximizes the average silhouette width, unless a specific number of clusters is provided by the user. The approach implemented in this package is based on the following publications: Rousseeuw (1987) <doi:10.1016/0377-0427(87)90125-7>; Ichino-Yaguchi (1994) <doi:10.1109/21.286391>; Arroyo-Maté-Roque (2006) <doi:10.1007/3-540-34416-0_7>.

r-bssm 2.0.3
Dependencies: pandoc@3.7.0.2
Propagated dependencies: r-tidyr@1.3.2 r-sitmo@2.0.2 r-rlang@1.2.0 r-rcpparmadillo@15.2.6-1 r-rcpp@1.1.1-1.1 r-ramcmc@0.1.2 r-posterior@1.7.0 r-dplyr@1.2.1 r-diagis@0.2.3 r-coda@0.19-4.1 r-checkmate@2.3.4 r-bayesplot@1.15.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/helske/bssm
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Inference of Non-Linear and Non-Gaussian State Space Models
Description:

Efficient methods for Bayesian inference of state space models via Markov chain Monte Carlo (MCMC) based on parallel importance sampling type weighted estimators (Vihola, Helske, and Franks, 2020, <doi:10.1111/sjos.12492>), particle MCMC, and its delayed acceptance version. Gaussian, Poisson, binomial, negative binomial, and Gamma observation densities and basic stochastic volatility models with linear-Gaussian state dynamics, as well as general non-linear Gaussian models and discretised diffusion models are supported. See Helske and Vihola (2021, <doi:10.32614/RJ-2021-103>) for details.

r-batata 0.2.1
Propagated dependencies: r-remotes@2.5.0 r-purrr@1.2.2 r-lubridate@1.9.5 r-jsonlite@2.0.0 r-glue@1.8.1 r-fs@2.1.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/feddelegrand7/batata
Licenses: Expat
Build system: r
Synopsis: Managing Packages Removal and Installation
Description:

Allows the user to manage easily R packages removal and installation. It offers many functions to display installed packages according to specific dates and removes them if needed. The user is always prompted when running the removal functions in order to confirm the required action. It also provides functions that will install Github starred R packages whether available on CRAN or not.

r-bigutilsr 0.3.11
Propagated dependencies: r-rspectra@0.16-2 r-robustbase@0.99-7 r-rcppeigen@0.3.4.0.2 r-rcpparmadillo@15.2.6-1 r-rcpp@1.1.1-1.1 r-nabor@0.5.0 r-bigparallelr@0.3.2 r-bigassertr@0.1.7
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/privefl/bigutilsr
Licenses: GPL 3
Build system: r
Synopsis: Utility Functions for Large-scale Data
Description:

Utility functions for large-scale data. For now, package bigutilsr mainly includes functions for outlier detection and unbiased PCA projection.

r-basecamb 1.1.5
Propagated dependencies: r-survival@3.8-6 r-sae@1.3 r-purrr@1.2.2 r-mice@3.19.0 r-mass@7.3-65 r-hmisc@5.2-5 r-dplyr@1.2.1 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://CRAN.R-project.org/package=basecamb
Licenses: GPL 3+
Build system: r
Synopsis: Utilities for Streamlined Data Import, Imputation and Modelling
Description:

This package provides functions streamlining the data analysis workflow: Outsourcing data import, renaming and type casting to a *.csv. Manipulating imputed datasets and fitting models on them. Summarizing models.

r-bdlnm 0.1.1
Propagated dependencies: r-tsmodel@0.6-2 r-dlnm@2.4.10 r-crs@0.15-43 r-cli@3.6.6
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/pasahe/bdlnm
Licenses: GPL 3+
Build system: r
Synopsis: Bayesian Distributed Lag Non-Linear Models (B-DLNM)
Description:

This package provides a Bayesian framework for estimating distributed lag linear and non-linear models. Model fitting is implemented using Integrated Nested Laplace Approximation (R package INLA'), together with prediction and visualization of exposure-lag-response associations. Additional functions allow estimation of optimal exposure values (e.g., minimum mortality temperature) and computation of attributable fractions and numbers. Models with crossbasis or onebasis terms are supported (R package dlnm').

r-blsloadr 0.4.6
Propagated dependencies: r-zoo@1.8-15 r-tigris@2.2.1 r-tidyselect@1.2.1 r-stringr@1.6.0 r-sf@1.1-1 r-rvest@1.0.5 r-rstudioapi@0.18.0 r-readxl@1.5.0 r-lubridate@1.9.5 r-httr@1.4.8 r-htmltools@0.5.9 r-dplyr@1.2.1 r-data-table@1.18.4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://schmidtdetr.github.io/BLSloadR/
Licenses: Expat
Build system: r
Synopsis: Download Time Series Data from the U.S. Bureau of Labor Statistics
Description:

These functions provide a convenient interface for downloading data from the U.S. Bureau of Labor Statistics <https://www.bls.gov>. The functions in this package utilize flat files produced by the Bureau of Labor Statistics, which contain full series history. These files include employment, unemployment, wages, prices, industry and occupational data at a national, state, and sub-state level, depending on the series. Individual functions are included for those programs which have data available at the state level. The core functions provide direct access to the Current Employment Statistics (CES) <https://www.bls.gov/ces/>, Local Area Unemployment Statistics (LAUS) <https://www.bls.gov/lau/>, Occupational Employment and Wage Statistics (OEWS) <https://www.bls.gov/oes/> and Alternative Measures of Labor Underutilization (SALT) <https://www.bls.gov/lau/stalt.htm> data produced by the Bureau of Labor Statistics.

r-bayestools 0.3.0
Propagated dependencies: r-rlang@1.2.0 r-rdpack@2.6.6 r-mvtnorm@1.3-7 r-ggplot2@4.0.3 r-extradistr@1.10.0.4 r-coda@0.19-4.1 r-bridgesampling@1.2-1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://fbartos.github.io/BayesTools/
Licenses: GPL 3
Build system: r
Synopsis: Tools for Bayesian Analyses
Description:

This package provides tools for conducting Bayesian analyses and Bayesian model averaging (Kass and Raftery, 1995, <doi:10.1080/01621459.1995.10476572>, Hoeting et al., 1999, <doi:10.1214/ss/1009212519>). The package contains functions for creating a wide range of prior distribution objects, mixing posterior samples from JAGS and Stan models, plotting posterior distributions, and etc... The tools for working with prior distribution span from visualization, generating JAGS and bridgesampling syntax to basic functions such as rng, quantile, and distribution functions.

r-bibnets 0.6.0
Propagated dependencies: r-matrix@1.7-5
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/mohsaqr/bibnets
Licenses: Expat
Build system: r
Synopsis: Importing, Constructing, and Exporting Bibliometric Networks
Description:

Imports, constructs, and exports bibliometric networks from scholarly metadata. Reads Scopus', Web of Science', BibTeX', RIS', OpenAlex', Lens.org', Dimensions', and Crossref exports. Goes beyond standard co-networks with attention-weighted networks (lead, last, proximity, circular position weights), position-aware counting (harmonic, arithmetic, geometric, golden-ratio), similarity and dissimilarity normalisations, temporal networks with fixed, sliding, and cumulative windows, disparity-filter backbone extraction, historiograph construction, and local citation scoring. Methods described in López-Pernas, Saqr & Apiola (2023) <doi:10.1007/978-3-031-25336-2_5>.

Total packages: 73977