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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:

GET /api/packages?search=hello&page=1&limit=20

where search is your query, page is a page number and limit is a number of items on a single page. Pagination information (such as a number of pages and etc) is returned in response headers.

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


r-bootstepaic 1.4-0
Propagated dependencies: r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bootStepAIC
Licenses: GPL 2+
Build system: r
Synopsis: Bootstrap stepAIC
Description:

Model selection by bootstrapping the stepAIC() procedure.

r-bayesiantreg 1.0.1
Propagated dependencies: r-mvtnorm@1.3-3 r-matrix@1.7-4 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=Bayesiantreg
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian t Regression for Modeling Mean and Scale Parameters
Description:

This package performs Bayesian t Regression where mean and scale parameters are modeling by lineal regression structures, and the degrees of freedom parameters are estimated.

r-bayesgrowth 1.0.0
Propagated dependencies: r-tidybayes@3.0.7 r-tibble@3.3.0 r-stanheaders@2.32.10 r-rstantools@2.5.0 r-rstan@2.32.7 r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-loo@2.8.0 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-bh@1.87.0-1 r-bayesplot@1.14.0 r-aquaticlifehistory@1.0.6
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/jonathansmart/BayesGrowth
Licenses: GPL 3
Build system: r
Synopsis: Estimate Fish Growth Using MCMC Analysis
Description:

Estimate fish length-at-age models using MCMC analysis with rstan models. This package allows a multimodel approach to growth fitting to be applied to length-at-age data and is supported by further analyses to determine model selection and result presentation. The core methods of this package are presented in Smart and Grammer (2021) "Modernising fish and shark growth curves with Bayesian length-at-age models". PLOS ONE 16(2): e0246734 <doi:10.1371/journal.pone.0246734>.

r-bindata 0.9-23
Propagated dependencies: r-mvtnorm@1.3-3 r-e1071@1.7-16
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bindata
Licenses: GPL 2
Build system: r
Synopsis: Generation of Artificial Binary Data
Description:

Generation of correlated artificial binary data.

r-bayesmultimode 0.7.4
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-sn@2.1.1 r-rdpack@2.6.4 r-posterior@1.6.1 r-mvtnorm@1.3-3 r-mcmcglmm@2.36 r-magrittr@2.0.4 r-gtools@3.9.5 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-bayesplot@1.14.0 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/paullabonne/BayesMultiMode
Licenses: GPL 3+
Build system: r
Synopsis: Bayesian Mode Inference
Description:

This package provides a two-step Bayesian approach for mode inference following Cross, Hoogerheide, Labonne and van Dijk (2024) <doi:10.1016/j.econlet.2024.111579>). First, a mixture distribution is fitted on the data using a sparse finite mixture (SFM) Markov chain Monte Carlo (MCMC) algorithm. The number of mixture components does not have to be known; the size of the mixture is estimated endogenously through the SFM approach. Second, the modes of the estimated mixture at each MCMC draw are retrieved using algorithms specifically tailored for mode detection. These estimates are then used to construct posterior probabilities for the number of modes, their locations and uncertainties, providing a powerful tool for mode inference.

r-boggy 0.0.1
Propagated dependencies: r-tibble@3.3.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://rmagno.eu/boggy/
Licenses: FSDG-compatible
Build system: r
Synopsis: Real-Time PCR Data Sets by Boggy et al. (2010)
Description:

Real-time quantitative polymerase chain reaction (qPCR) data sets by Boggy et al. (2008) <doi:10.1371/journal.pone.0012355>. This package provides a dilution series for one PCR target: a random sequence that minimizes secondary structure and off-target primer binding. The data set is a six-point, ten-fold dilution series. For each concentration there are two replicates. Each amplification curve is 40 cycles long. Original raw data file: <https://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0012355.s004>.

r-basinet 0.0.5
Propagated dependencies: r-rweka@0.4-46 r-rmcfs@1.3.6 r-rjava@1.0-11 r-randomforest@4.7-1.2 r-igraph@2.2.1 r-biostrings@2.78.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BASiNET
Licenses: GPL 3
Build system: r
Synopsis: Classification of RNA Sequences using Complex Network 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 threshold for the purpose of making a classification between the classes of the sequences. There are four data present in the BASiNET package, "sequences", "sequences2", "sequences-predict" and "sequences2-predict" with 11, 10, 11 and 11 sequences respectively. 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. The BASiNET was published on Nucleic Acids Research, (ITO, Eric; KATAHIRA, Isaque; VICENTE, Fábio; PEREIRA, Felipe; LOPES, Fabrà cio, 2018) <doi:10.1093/nar/gky462>.

r-bayesbekk 0.1.1
Propagated dependencies: r-mvtnorm@1.3-3 r-mts@1.2.1 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BayesBEKK
Licenses: GPL 3
Build system: r
Synopsis: Bayesian Estimation of Bivariate Volatility Model
Description:

The Multivariate Generalized Autoregressive Conditional Heteroskedasticity (MGARCH) models are used for modelling the volatile multivariate data sets. In this package a variant of MGARCH called BEKK (Baba, Engle, Kraft, Kroner) proposed by Engle and Kroner (1995) <http://www.jstor.org/stable/3532933> has been used to estimate the bivariate time series data using Bayesian technique.

r-bivariate-pareto 1.0.3
Propagated dependencies: r-compound-cox@3.33
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=Bivariate.Pareto
Licenses: GPL 2
Build system: r
Synopsis: Bivariate Pareto Models
Description:

Perform competing risks analysis under bivariate Pareto models. See Shih et al. (2019) <doi:10.1080/03610926.2018.1425450> for details.

r-brickset 2026.0.0
Propagated dependencies: r-piggyback@0.1.5 r-jsonlite@2.0.0 r-httr@1.4.7 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/jbryer/brickset
Licenses: GPL 3+
Build system: r
Synopsis: Interface with the Brickset API for Getting Data About LEGO Sets
Description:

Interface with the Brickset API <https://brickset.com/article/52664/api-version-3-documentation> for getting data about LEGO sets. Data sets that can be used for teaching and learning without the need of a Brickset account and API key are also included. Includes all LEGO since through the end of 2025.

r-bwquant 0.1.0
Propagated dependencies: r-quantreg@6.1 r-nleqslv@3.3.5 r-kernsmooth@2.23-26
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BwQuant
Licenses: GPL 2
Build system: r
Synopsis: Bandwidth Selectors for Local Linear Quantile Regression
Description:

Bandwidth selectors for local linear quantile regression, including cross-validation and plug-in methods. The local linear quantile regression estimate is also implemented.

r-brainr 1.7.0
Propagated dependencies: r-rgl@1.3.31 r-oro-nifti@0.11.4 r-misc3d@0.9-1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=brainR
Licenses: GPL 2
Build system: r
Synopsis: Helper Functions to 'misc3d' and 'rgl' Packages for Brain Imaging
Description:

This includes functions for creating 3D and 4D images using WebGL', rgl', and JavaScript commands. This package relies on the X toolkit ('XTK', <https://github.com/xtk/X#readme>).

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@0.6-20 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-bstrl 1.0.2
Propagated dependencies: r-foreach@1.5.2 r-extradistr@1.10.0 r-doparallel@1.0.17 r-brl@0.1.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bstrl
Licenses: Expat
Build system: r
Synopsis: Bayesian Streaming Record Linkage
Description:

Perform record linkage on streaming files using recursive Bayesian updating.

r-bspmma 0.1-2
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bspmma
Licenses: GPL 2
Build system: r
Synopsis: Bayesian Semiparametric Models for Meta-Analysis
Description:

The main functions carry out Gibbs sampler routines for nonparametric and semiparametric Bayesian models for random effects meta-analysis.

r-bioprobability 1.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BioProbability
Licenses: GPL 2
Build system: r
Synopsis: Probability in Biostatistics
Description:

Several tools for analyzing diagnostic tests and 2x2 contingency tables are provided. In particular, positive and negative predictive values for a diagnostic tests can be calculated from prevalence, sensitivity and specificity values. For contingency tables, relative risk and odds ratio measures are estimated. Furthermore, confidence intervals are provided.

r-bayesianplatformdesigntimetrend 1.2.3
Propagated dependencies: r-stringr@1.6.0 r-stanheaders@2.32.10 r-rstantools@2.5.0 r-rstan@2.32.7 r-reshape@0.8.10 r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-rcolorbrewer@1.1-3 r-matrixstats@1.5.0 r-lhs@1.2.0 r-lagp@1.5-9 r-iterators@1.0.14 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-foreach@1.5.2 r-doparallel@1.0.17 r-boot@1.3-32 r-biocmanager@1.30.27 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/ZXW834/BayesianPlatformDesignTimeTrend
Licenses: Expat
Build system: r
Synopsis: Simulate and Analyse Bayesian Platform Trial with Time Trend
Description:

Simulating the sequential multi-arm multi-stage or platform trial with Bayesian approach using the rstan package, which provides the R interface for the Stan. This package supports fixed ratio and Bayesian adaptive randomization approaches for randomization. Additionally, it allows for the study of time trend problems in platform trials. There are demos available for a multi-arm multi-stage trial with two different null scenarios, as well as for Bayesian trial cutoff screening. The Bayesian adaptive randomisation approaches are described in: Trippa et al. (2012) <doi:10.1200/JCO.2011.39.8420> and Wathen et al. (2017) <doi:10.1177/1740774517692302>. The randomisation algorithm is described in: Zhao W <doi:10.1016/j.cct.2015.06.008>. The analysis methods of time trend effect in platform trial are described in: Saville et al. (2022) <doi:10.1177/17407745221112013> and Bofill Roig et al. (2022) <doi:10.1186/s12874-022-01683-w>.

r-bayesdecon 0.1.4
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mvtnorm@1.3-3 r-msm@1.8.2 r-ks@1.15.1 r-corpcor@1.6.10
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BayesDecon
Licenses: GPL 2+
Build system: r
Synopsis: Density Deconvolution Using Bayesian Semiparametric Methods
Description:

Estimates the density of a variable in a measurement error setup, potentially with an excess of zero values. For more details see Sarkar (2022) <doi:10.1080/01621459.2020.1782220>.

r-boiwsa 1.1.4
Propagated dependencies: r-tidyr@1.3.1 r-rlang@1.1.6 r-lubridate@1.9.4 r-hmisc@5.2-4 r-gridextra@2.3 r-ggplot2@4.0.1 r-forecast@8.24.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/timginker/boiwsa
Licenses: Expat
Build system: r
Synopsis: Seasonal Adjustment of Weekly Data
Description:

Perform seasonal adjustment and forecasting of weekly data. The package provides a user-friendly interface for computing seasonally adjusted estimates and forecasts of weekly time series and includes functions for the construction of country-specific prior adjustment variables, as well as diagnostic tools to assess the quality of the adjustments. The methodology is described in more detail in Ginker (2024) <doi:10.13140/RG.2.2.12221.44000>.

r-boxplotdbl 1.4.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=boxplotdbl
Licenses: Expat
Build system: r
Synopsis: Double Box Plot for Two-Axes Correlation
Description:

Correlation chart of two set (x and y) of data. Using Quartiles with boxplot style. Visualize the effect of factor.

r-bayesssm 0.7.1
Propagated dependencies: r-rcpp@1.1.0 r-mass@7.3-65 r-future-apply@1.20.0 r-future@1.68.0 r-dplyr@1.1.4 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/BjarkeHautop/bayesSSM
Licenses: Expat
Build system: r
Synopsis: Bayesian Methods for State Space Models
Description:

This package implements methods for Bayesian analysis of State Space Models. Includes implementations of the Particle Marginal Metropolis-Hastings algorithm described in Andrieu et al. (2010) <doi:10.1111/j.1467-9868.2009.00736.x> and automatic tuning inspired by Pitt et al. (2012) <doi:10.1016/j.jeconom.2012.06.004> and J. Dahlin and T. B. Schön (2019) <doi:10.18637/jss.v088.c02>.

r-bayesat 0.1.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BayesAT
Licenses: GPL 3
Build system: r
Synopsis: Bayesian Adaptive Trial
Description:

Bayesian adaptive trial algorithm implements multiple-stage interim analysis. Package includes data generating function, and Bayesian hypothesis testing function.

r-bayespo 0.5.0
Propagated dependencies: r-rcppprogress@0.4.2 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bayesPO
Licenses: GPL 3
Build system: r
Synopsis: Bayesian Inference for Presence-Only Data
Description:

Presence-Only data is best modelled with a Point Process Model. The work of Moreira and Gamerman (2022) <doi:10.1214/21-AOAS1569> provides a way to use exact Bayesian inference to model this type of data, which is implemented in this package.

r-boptbd 1.0.7
Propagated dependencies: r-matrix@1.7-4 r-mass@7.3-65 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=Boptbd
Licenses: GPL 2
Build system: r
Synopsis: Bayesian Optimal Block Designs
Description:

Computes Bayesian A- and D-optimal block designs under the linear mixed effects model settings using block/array exchange algorithm of Debusho, Gemechu and Haines (2018) <doi:10.1080/03610918.2018.1429617> and Gemechu, Debusho and Haines (2025) <doi:10.5539/ijsp.v14n1p50> where the interest is in a comparison of all possible elementary treatment contrasts. The package also provides an optional method of using the graphical user interface (GUI) R package tcltk to ensure that it is user friendly.

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