_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
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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-bmisc 1.4.8
Propagated dependencies: r-tidyr@1.3.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-dplyr@1.1.4 r-data-table@1.17.8 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://bcallaway11.github.io/BMisc/
Licenses: GPL 2
Synopsis: Miscellaneous Functions for Panel Data, Quantiles, and Printing Results
Description:

These are miscellaneous functions for working with panel data, quantiles, and printing results. For panel data, the package includes functions for making a panel data balanced (that is, dropping missing individuals that have missing observations in any time period), converting id numbers to row numbers, and to treat repeated cross sections as panel data under the assumption of rank invariance. For quantiles, there are functions to make distribution functions from a set of data points (this is particularly useful when a distribution function is created in several steps), to combine distribution functions based on some external weights, and to invert distribution functions. Finally, there are several other miscellaneous functions for obtaining weighted means, weighted distribution functions, and weighted quantiles; to generate summary statistics and their differences for two groups; and to add or drop covariates from formulas.

r-bain 0.2.11
Propagated dependencies: r-lavaan@0.6-20
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://informative-hypotheses.sites.uu.nl/software/bain/
Licenses: GPL 3+
Synopsis: Bayes Factors for Informative Hypotheses
Description:

Computes approximated adjusted fractional Bayes factors for equality, inequality, and about equality constrained hypotheses. For a tutorial on this method, see Hoijtink, Mulder, van Lissa, & Gu, (2019) <doi:10.1037/met0000201>. For applications in structural equation modeling, see: Van Lissa, Gu, Mulder, Rosseel, Van Zundert, & Hoijtink, (2021) <doi:10.1080/10705511.2020.1745644>. For the statistical underpinnings, see Gu, Mulder, and Hoijtink (2018) <doi:10.1111/bmsp.12110>; Hoijtink, Gu, & Mulder, J. (2019) <doi:10.1111/bmsp.12145>; Hoijtink, Gu, Mulder, & Rosseel, (2019) <doi:10.31234/osf.io/q6h5w>.

r-bivrp 1.2-2
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=bivrp
Licenses: GPL 2+
Synopsis: Bivariate Residual Plots with Simulation Polygons
Description:

Generates bivariate residual plots with simulation polygons for any diagnostics and bivariate model from which functions to extract the desired diagnostics, simulate new data and refit the models are available.

r-bspm 0.5.7
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran4linux.github.io/bspm/
Licenses: Expat
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-binr 1.1.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/jabiru/binr
Licenses: ASL 2.0
Synopsis: Cut Numeric Values into Evenly Distributed Groups
Description:

Implementation of algorithms for cutting numerical values exhibiting a potentially highly skewed distribution into evenly distributed groups (bins). This functionality can be applied for binning discrete values, such as counts, as well as for discretization of continuous values, for example, during generation of features used in machine learning algorithms.

r-bda 19.0.0
Propagated dependencies: r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bda
Licenses: FSDG-compatible
Synopsis: Binned Data Analysis
Description:

Algorithms developed for binned data analysis, gene expression data analysis and measurement error models for ordinal data analysis.

r-bamlss 1.2-5
Propagated dependencies: r-survival@3.8-3 r-sp@2.2-0 r-mvtnorm@1.3-3 r-mgcv@1.9-4 r-mba@0.1-2 r-matrix@1.7-4 r-formula@1.2-5 r-distributions3@0.2.3 r-colorspace@2.1-2 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: http://www.bamlss.org/
Licenses: GPL 2 GPL 3
Synopsis: Bayesian Additive Models for Location, Scale, and Shape (and Beyond)
Description:

Infrastructure for estimating probabilistic distributional regression models in a Bayesian framework. The distribution parameters may capture location, scale, shape, etc. and every parameter may depend on complex additive terms (fixed, random, smooth, spatial, etc.) similar to a generalized additive model. The conceptual and computational framework is introduced in Umlauf, Klein, Zeileis (2019) <doi:10.1080/10618600.2017.1407325> and the R package in Umlauf, Klein, Simon, Zeileis (2021) <doi:10.18637/jss.v100.i04>.

r-biometryassist 1.3.3
Propagated dependencies: r-xml2@1.5.0 r-stringi@1.8.7 r-scales@1.4.0 r-rlang@1.1.6 r-pracma@2.4.6 r-multcompview@0.1-10 r-lattice@0.22-7 r-ggplot2@4.0.1 r-emmeans@2.0.0 r-curl@7.0.0 r-cowplot@1.2.0 r-askpass@1.2.1 r-agricolae@1.3-7
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://biometryhub.github.io/biometryassist/
Licenses: Expat
Synopsis: Functions to Assist Design and Analysis of Agronomic Experiments
Description:

This package provides functions to aid in the design and analysis of agronomic and agricultural experiments through easy access to documentation and helper functions, especially for users who are learning these concepts. While not required for most functionality, this package enhances the `asreml` package which provides a computationally efficient algorithm for fitting mixed models using Residual Maximum Likelihood. It is a commercial package that can be purchased as asreml-R from VSNi <https://vsni.co.uk/>, who will supply a zip file for local installation/updating (see <https://asreml.kb.vsni.co.uk/>).

r-bayesxsrc 3.0-6
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://www.uni-goettingen.de/de/bayesx/550513.html
Licenses: GPL 2 GPL 3
Synopsis: Distribution of the 'BayesX' C++ Sources
Description:

BayesX performs Bayesian inference in structured additive regression (STAR) models. The R package BayesXsrc provides the BayesX command line tool for easy installation. A convenient R interface is provided in package R2BayesX.

r-breakpoints 1.2
Propagated dependencies: r-zoo@1.8-14 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=BreakPoints
Licenses: GPL 3
Synopsis: Identify Breakpoints in Series of Data
Description:

Compute Buishand Range Test, Pettit Test, SNHT, Student t-test, and Mann-Whitney Rank Test, to identify breakpoints in series. For all functions NA is allowed. Since all of the mention methods identify only one breakpoint in a series, a general function to look for N breakpoint is given. Also, the Yamamoto test for climate jump is available. Alexandersson, H. (1986) <doi:10.1002/joc.3370060607>, Buishand, T. (1982) <doi:10.1016/0022-1694(82)90066-X>, Hurtado, S. I., Zaninelli, P. G., & Agosta, E. A. (2020) <doi:10.1016/j.atmosres.2020.104955>, Mann, H. B., Whitney, D. R. (1947) <doi:10.1214/aoms/1177730491>, Pettitt, A. N. (1979) <doi:10.2307/2346729>, Ruxton, G. D., jul (2006) <doi:10.1093/beheco/ark016>, Yamamoto, R., Iwashima, T., Kazadi, S. N., & Hoshiai, M. (1985) <doi:10.2151/jmsj1965.63.6_1157>.

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+
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-bispdep 1.0-2
Propagated dependencies: r-spdep@1.4-1 r-spdata@2.3.4 r-spatialreg@1.4-2 r-sp@2.2-0 r-sf@1.0-23 r-rcolorbrewer@1.1-3 r-ggplot2@4.0.1 r-combinat@0.0-8 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/carlosm77/bispdep
Licenses: GPL 2+
Synopsis: Statistical Tools for Bivariate Spatial Dependence Analysis
Description:

This package provides a collection of functions to test spatial autocorrelation between variables, including Moran I, Geary C and Getis G together with scatter plots, functions for mapping and identifying clusters and outliers, functions associated with the moments of the previous statistics that will allow testing whether there is bivariate spatial autocorrelation, and a function that allows identifying (visualizing neighbours) on the map, the neighbors of any region once the scheme of the spatial weights matrix has been established.

r-birdring 1.6
Propagated dependencies: r-raster@3.6-32 r-lazydata@1.1.0 r-ks@1.15.1 r-geosphere@1.5-20
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=birdring
Licenses: GPL 2
Synopsis: Methods to Analyse Ring Re-Encounter Data
Description:

R functions to read EURING data and analyse re-encounter data of birds marked by metal rings. For a tutorial, go to <doi:10.1080/03078698.2014.933053>.

r-bs4dash 2.3.5
Propagated dependencies: r-waiter@0.2.5-1.927501b r-shiny@1.11.1 r-rlang@1.1.6 r-lifecycle@1.0.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-httpuv@1.6.16 r-htmltools@0.5.8.1 r-fresh@0.2.2 r-cli@3.6.5 r-bslib@0.9.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/RinteRface/bs4Dash
Licenses: GPL 2+ FSDG-compatible
Synopsis: 'Bootstrap 4' Version of 'shinydashboard'
Description:

Make Bootstrap 4 Shiny dashboards. Use the full power of AdminLTE3', a dashboard template built on top of Bootstrap 4 <https://github.com/ColorlibHQ/AdminLTE>.

r-branchingprocess 0.1.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/EpiForeSITE/branchingprocess
Licenses: Expat
Synopsis: Calculate Outbreak Probabilities for a Branching Process Model
Description:

Quantify outbreak risk posed by individual importers of a transmissible pathogen. Input parameters of negative binomial offspring distributions for the number of transmissions from each infected individual and initial number of infected. Calculate probabilities of final outbreak size and generations of transmission, as described in Toth et al. (2015) <doi:10.3201/eid2108.150170> and Toth et al. (2016) <doi:10.1016/j.epidem.2016.04.002>.

r-bumblebee 0.1.0
Propagated dependencies: r-rmarkdown@2.30 r-magrittr@2.0.4 r-hmisc@5.2-4 r-gtools@3.9.5 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://magosil86.github.io/bumblebee/
Licenses: Expat
Synopsis: Quantify Disease Transmission Within and Between Population Groups
Description:

This package provides a simple tool to quantify the amount of transmission of an infectious disease of interest occurring within and between population groups. bumblebee uses counts of observed directed transmission pairs, identified phylogenetically from deep-sequence data or from epidemiological contacts, to quantify transmission flows within and between population groups accounting for sampling heterogeneity. Population groups might include: geographical areas (e.g. communities, regions), demographic groups (e.g. age, gender) or arms of a randomized clinical trial. See the bumblebee website for statistical theory, documentation and examples <https://magosil86.github.io/bumblebee/>.

r-biplotbootgui 1.3
Propagated dependencies: r-tkrplot@0.0-30 r-tcltk2@1.6.1 r-shapes@1.2.8 r-rgl@1.3.31 r-matlib@1.0.1 r-mass@7.3-65 r-dendroextras@0.2.3 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=biplotbootGUI
Licenses: GPL 2+
Synopsis: Bootstrap on Classical Biplots and Clustering Disjoint Biplot
Description:

This package provides a GUI with which the user can construct and interact with Bootstrap methods on Classical Biplots and with Clustering and/or Disjoint Biplot. This GUI is also aimed for estimate any numerical data matrix using the Clustering and Disjoint Principal component (CDPCA) methodology.

r-bin2norm 0.1.0
Propagated dependencies: r-statmod@1.5.1 r-rstan@2.32.7 r-lme4@1.1-37
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bin2norm
Licenses: Expat
Synopsis: Hierarchical Probit Estimation for Dichotomized Data
Description:

This package provides likelihood-based and hierarchical estimation methods for thresholded (binomial-probit) data. Supports fixed-mean and random-mean models with maximum likelihood estimation (MLE), generalized linear mixed model (GLMM), and Bayesian Markov chain Monte Carlo (MCMC) implementations. For methodological background, see Albert and Chib (1993) <doi:10.1080/01621459.1993.10476321> and McCulloch (1994) <doi:10.2307/2297959>.

r-blogdown 1.22
Propagated dependencies: r-yaml@2.3.10 r-xfun@0.54 r-servr@0.32 r-rmarkdown@2.30 r-later@1.4.4 r-knitr@1.50 r-jsonlite@2.0.0 r-httpuv@1.6.16 r-htmltools@0.5.8.1 r-bookdown@0.45
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/rstudio/blogdown
Licenses: GPL 3
Synopsis: Create Blogs and Websites with R Markdown
Description:

Write blog posts and web pages in R Markdown. This package supports the static site generator Hugo (<https://gohugo.io>) best, and it also supports Jekyll (<https://jekyllrb.com>) and Hexo (<https://hexo.io>).

r-bdribs 1.0.4
Propagated dependencies: r-rjags@4-17
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bdribs
Licenses: GPL 2
Synopsis: Bayesian Detection of Potential Risk Using Inference on Blinded Safety Data
Description:

This package implements Bayesian inference to detect signal from blinded clinical trial when total number of adverse events of special concerns and total risk exposures from all patients are available in the study. For more details see the article by Mukhopadhyay et. al. (2018) titled Bayesian Detection of Potential Risk Using Inference on Blinded Safety Data', in Pharmaceutical Statistics (to appear).

r-bayesmfsurv 0.1.0
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mvtnorm@1.3-3 r-mcmcpack@1.7-1 r-fastgp@1.2 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=BayesMFSurv
Licenses: Expat
Synopsis: Bayesian Misclassified-Failure Survival Model
Description:

This package contains a split population survival estimator that models the misclassification probability of failure versus right-censored events. The split population survival estimator is described in Bagozzi et al. (2019) <doi:10.1017/pan.2019.6>.

r-bushtucker 0.1.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://chrisbrownlie.github.io/bushtucker/
Licenses: Expat
Synopsis: 'I'm a Celebrity Get Me Out of Here' Data
Description:

Data on the first 24 seasons of the UK TV show I'm a Celebrity, Get Me Out of Here', broadcast from 2002-2024. Taken from the Wikipedia pages for each season and the main page available at <https://en.wikipedia.org/wiki/I%27m_a_Celebrity...Get_Me_Out_of_Here!_(British_TV_series)>.

r-beautier 2.6.12
Propagated dependencies: r-stringr@1.6.0 r-seqinr@4.2-36 r-rlang@1.1.6 r-rappdirs@0.3.3 r-purrr@1.2.0 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://docs.ropensci.org/beautier/
Licenses: GPL 3
Synopsis: 'BEAUti' from R
Description:

BEAST2 (<https://www.beast2.org>) is a widely used Bayesian phylogenetic tool, that uses DNA/RNA/protein data and many model priors to create a posterior of jointly estimated phylogenies and parameters. BEAUti 2 (which is part of BEAST2') is a GUI tool that allows users to specify the many possible setups and generates the XML file BEAST2 needs to run. This package provides a way to create BEAST2 input files without active user input, but using R function calls instead.

r-bcrocsurface 1.0-6
Propagated dependencies: r-rgl@1.3.31 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-nnet@7.3-20 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/toduckhanh/bcROCsurface
Licenses: GPL 3
Synopsis: Bias-Corrected Methods for Estimating the ROC Surface of Continuous Diagnostic Tests
Description:

The bias-corrected estimation methods for the receiver operating characteristics ROC surface and the volume under ROC surfaces (VUS) under missing at random (MAR) assumption.

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