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    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
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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-bhmbasket 0.9.5
Propagated dependencies: r-r2jags@0.8-9 r-foreach@1.5.2 r-dorng@1.8.6.2
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://CRAN.R-project.org/package=bhmbasket
Licenses: GPL 3
Build system: r
Synopsis: Bayesian Hierarchical Models for Basket Trials
Description:

This package provides functions for the evaluation of basket trial designs with binary endpoints. Operating characteristics of a basket trial design are assessed by simulating trial data according to scenarios, analyzing the data with Bayesian hierarchical models (BHMs), and assessing decision probabilities on stratum and trial-level based on Go / No-go decision making. The package is build for high flexibility regarding decision rules, number of interim analyses, number of strata, and recruitment. The BHMs proposed by Berry et al. (2013) <doi:10.1177/1740774513497539> and Neuenschwander et al. (2016) <doi:10.1002/pst.1730>, as well as a model that combines both approaches are implemented. Functions are provided to implement Bayesian decision rules as for example proposed by Fisch et al. (2015) <doi:10.1177/2168479014533970>. In addition, posterior point estimates (mean/median) and credible intervals for response rates and some model parameters can be calculated. For simulated trial data, bias and mean squared errors of posterior point estimates for response rates can be provided.

r-bsda 1.2.2
Propagated dependencies: r-lattice@0.22-7 r-e1071@1.7-16
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/alanarnholt/BSDA
Licenses: GPL 3
Build system: r
Synopsis: Basic Statistics and Data Analysis
Description:

Data sets for book "Basic Statistics and Data Analysis" by Larry J. Kitchens.

r-bayeswatch 0.1.4
Propagated dependencies: r-rcppeigen@0.3.4.0.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-matrix@1.7-4 r-mass@7.3-65 r-hotelling@1.0-8 r-gridextra@2.3 r-ggplot2@4.0.1 r-ess@1.1.2.1 r-cholwishart@1.1.4 r-bh@1.87.0-1 r-bdgraph@2.74
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bayesWatch
Licenses: GPL 3
Build system: r
Synopsis: Bayesian Change-Point Detection for Process Monitoring with Fault Detection
Description:

Bayes Watch fits an array of Gaussian Graphical Mixture Models to groupings of homogeneous data in time, called regimes, which are modeled as the observed states of a Markov process with unknown transition probabilities. In doing so, Bayes Watch defines a posterior distribution on a vector of regime assignments, which gives meaningful expressions on the probability of every possible change-point. Bayes Watch also allows for an effective and efficient fault detection system that assesses what features in the data where the most responsible for a given change-point. For further details, see: Alexander C. Murph et al. (2023) <doi:10.48550/arXiv.2310.02940>.

r-bidimregression 2.0.1
Propagated dependencies: r-formula@1.2-5
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://CRAN.R-project.org/package=BiDimRegression/
Licenses: GPL 3
Build system: r
Synopsis: Calculates the Bidimensional Regression Between Two 2D Configurations
Description:

Calculates the bidimensional regression between two 2D configurations following the approach by Tobler (1965).

r-btrm 0.2.0
Propagated dependencies: r-proc@1.19.0.1 r-mass@7.3-65 r-arm@1.14-4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=btrm
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Treed Regression Model for Personalized Prediction and Precision Diagnostics
Description:

Generalization of the Bayesian classification and regression tree (CART) model that partitions subjects into terminal nodes and tailors regression model to each terminal node.

r-bdscale 2.0.0
Propagated dependencies: r-scales@1.4.0 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: http://github.com/dvmlls/bdscale
Licenses: GPL 2
Build system: r
Synopsis: Remove Weekends and Holidays from ggplot2 Axes
Description:

This package provides a continuous date scale, omitting weekends and holidays.

r-blockstrap 1.0.0
Propagated dependencies: r-vctrs@0.6.5 r-rlang@1.1.6 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://numbats.github.io/blockstrap/
Licenses: Expat
Build system: r
Synopsis: Sample Dataframes by a Group
Description:

Sample dataframes by group, in the form of a block bootstrap'. Entire groups are returned allowing for a single observation to span multiple rows of the dataframe.

r-buoyant 0.1.0
Propagated dependencies: r-yaml@2.3.10 r-withr@3.0.2 r-ssh@0.9.4 r-renv@1.1.5 r-jsonlite@2.0.0 r-analogsea@1.0.7.2
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://posit-dev.github.io/buoyant/
Licenses: Expat
Build system: r
Synopsis: Deploy '_server.yml' Compliant Applications to 'DigitalOcean'
Description:

This package provides tools to deploy R web server applications that follow the _server.yml standard. This standard allows different R server frameworks ('plumber2', fiery', etc.) to be deployed using a common interface. The package supports deployment to DigitalOcean and includes validation tools to ensure _server.yml files are correctly formatted.

r-bipartited3 0.3.2
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rcolorbrewer@1.1-3 r-r2d3@0.2.6 r-purrr@1.2.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=bipartiteD3
Licenses: GPL 3
Build system: r
Synopsis: Interactive Bipartite Graphs
Description:

Generates interactive bipartite graphs using the D3 library. Designed for use with the bipartite analysis package. Includes open source viz-js library Adapted from examples at <https://bl.ocks.org/NPashaP> (released under GPL-3).

r-breakaway 4.8.4
Propagated dependencies: r-tibble@3.3.0 r-phyloseq@1.54.0 r-mass@7.3-65 r-magrittr@2.0.4 r-lme4@1.1-37 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://adw96.github.io/breakaway/
Licenses: GPL 2
Build system: r
Synopsis: Species Richness Estimation and Modeling
Description:

Understanding the drivers of microbial diversity is an important frontier of microbial ecology, and investigating the diversity of samples from microbial ecosystems is a common step in any microbiome analysis. breakaway is the premier package for statistical analysis of microbial diversity. breakaway implements the latest and greatest estimates of species richness, described in Willis and Bunge (2015) <doi:10.1111/biom.12332>, Willis et al. (2017) <doi:10.1111/rssc.12206>, and Willis (2016) <arXiv:1604.02598>, as well as the most commonly used estimates, including the objective Bayes approach described in Barger and Bunge (2010) <doi:10.1214/10-BA527>.

r-bunching 0.8.6
Propagated dependencies: r-tidyr@1.3.1 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-bb@2019.10-1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/mavpanos/bunching
Licenses: Expat
Build system: r
Synopsis: Estimate Bunching
Description:

Implementation of the bunching estimator for kinks and notches. Allows for flexible estimation of counterfactual (e.g. controlling for round number bunching, accounting for other bunching masses within bunching window, fixing bunching point to be minimum, maximum or median value in its bin, etc.). It produces publication-ready plots in the style followed since Chetty et al. (2011) <doi:10.1093/qje/qjr013>, with lots of functionality to set plot options.

r-binomialrf 0.1.0
Propagated dependencies: r-rlist@0.4.6.2 r-randomforest@4.7-1.2 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://www.biorxiv.org/content/10.1101/681973v1.abstract
Licenses: GPL 2
Build system: r
Synopsis: Binomial Random Forest Feature Selection
Description:

The binomialRF is a new feature selection technique for decision trees that aims at providing an alternative approach to identify significant feature subsets using binomial distributional assumptions (Rachid Zaim, S., et al. (2019)) <doi:10.1101/681973>. Treating each splitting variable selection as a set of exchangeable correlated Bernoulli trials, binomialRF then tests whether a feature is selected more often than by random chance.

r-baguette 1.1.0
Propagated dependencies: r-withr@3.0.2 r-tidyr@1.3.1 r-tibble@3.3.0 r-rsample@1.3.1 r-rpart@4.1.24 r-rlang@1.1.6 r-purrr@1.2.0 r-parsnip@1.3.3 r-magrittr@2.0.4 r-hardhat@1.4.2 r-generics@0.1.4 r-furrr@0.3.1 r-dplyr@1.1.4 r-dials@1.4.2 r-cli@3.6.5 r-c50@0.2.0 r-butcher@0.3.6
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://baguette.tidymodels.org
Licenses: Expat
Build system: r
Synopsis: Efficient Model Functions for Bagging
Description:

Tree- and rule-based models can be bagged (<doi:10.1007/BF00058655>) using this package and their predictions equations are stored in an efficient format to reduce the model objects size and speed.

r-bdesize 1.6
Propagated dependencies: r-ggplot2@4.0.1 r-fpow@0.0-3
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BDEsize
Licenses: GPL 2+
Build system: r
Synopsis: Efficient Determination of Sample Size in Balanced Design of Experiments
Description:

For a balanced design of experiments, this package calculates the sample size required to detect a certain standardized effect size, under a significance level. This package also provides three graphs; detectable standardized effect size vs power, sample size vs detectable standardized effect size, and sample size vs power, which show the mutual relationship between the sample size, power and the detectable standardized effect size. The detailed procedure is described in R. V. Lenth (2006-9) <https://homepage.divms.uiowa.edu/~rlenth/Power/>, Y. B. Lim (1998), M. A. Kastenbaum, D. G. Hoel and K. O. Bowman (1970) <doi:10.2307/2334851>, and Douglas C. Montgomery (2013, ISBN: 0849323312).

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
Build system: r
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.

r-boutroslab-plotting-general 7.1.5
Propagated dependencies: r-mass@7.3-65 r-latticeextra@0.6-31 r-lattice@0.22-7 r-hexbin@1.28.5 r-gtable@0.3.6 r-gridextra@2.3 r-e1071@1.7-16 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/uclahs-cds/package-BoutrosLab-plotting-general
Licenses: GPL 2
Build system: r
Synopsis: Functions to Create Publication-Quality Plots
Description:

This package contains several plotting functions such as barplots, scatterplots, heatmaps, as well as functions to combine plots and assist in the creation of these plots. These functions will give users great ease of use and customization options in broad use for biomedical applications, as well as general purpose plotting. Each of the functions also provides valid default settings to make plotting data more efficient and producing high quality plots with standard colour schemes simpler. All functions within this package are capable of producing plots that are of the quality to be presented in scientific publications and journals. P'ng et al.; BPG: Seamless, automated and interactive visualization of scientific data; BMC Bioinformatics 2019 <doi:10.1186/s12859-019-2610-2>.

r-bam 1.0.3
Propagated dependencies: r-mice@3.18.0 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=BaM
Licenses: GPL 2+
Build system: r
Synopsis: Functions and Datasets for "Bayesian Methods: A Social and Behavioral Sciences Approach"
Description:

This package provides functions and datasets for Jeff Gill: "Bayesian Methods: A Social and Behavioral Sciences Approach". First, Second, and Third Edition. Published by Chapman and Hall/CRC (2002, 2007, 2014) <doi:10.1201/b17888>.

r-bgfd 0.1
Propagated dependencies: r-adequacymodel@2.0.0
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BGFD
Licenses: GPL 2+
Build system: r
Synopsis: Bell-G and Complementary Bell-G Family of Distributions
Description:

Evaluates the probability density function, cumulative distribution function, quantile function, random numbers, survival function, hazard rate function, and maximum likelihood estimates for the following distributions: Bell exponential, Bell extended exponential, Bell Weibull, Bell extended Weibull, Bell-Fisk, Bell-Lomax, Bell Burr-XII, Bell Burr-X, complementary Bell exponential, complementary Bell extended exponential, complementary Bell Weibull, complementary Bell extended Weibull, complementary Bell-Fisk, complementary Bell-Lomax, complementary Bell Burr-XII and complementary Bell Burr-X distribution. Related work includes: a) Fayomi A., Tahir M. H., Algarni A., Imran M. and Jamal F. (2022). "A new useful exponential model with applications to quality control and actuarial data". Computational Intelligence and Neuroscience, 2022. <doi:10.1155/2022/2489998>. b) Alanzi, A. R., Imran M., Tahir M. H., Chesneau C., Jamal F. Shakoor S. and Sami, W. (2023). "Simulation analysis, properties and applications on a new Burr XII model based on the Bell-X functionalities". AIMS Mathematics, 8(3): 6970-7004. <doi:10.3934/math.2023352>. c) Algarni A. (2022). "Group Acceptance Sampling Plan Based on New Compounded Three-Parameter Weibull Model". Axioms, 11(9): 438. <doi:10.3390/axioms11090438>.

r-bigdatastatmeth 1.0.3
Dependencies: zlib@1.3.1
Propagated dependencies: r-rhdf5lib@1.32.0 r-rhdf5@2.54.0 r-rcurl@1.98-1.17 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-data-table@1.17.8 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BigDataStatMeth
Licenses: Expat
Build system: r
Synopsis: Tools and Infrastructure for Developing 'Scalable' 'HDF5'-Based Methods
Description:

This package provides a framework for scalable statistical computing on large on-disk matrices stored in HDF5 files. It provides efficient block-wise implementations of core linear-algebra operations (matrix multiplication, SVD, PCA, QR decomposition, and canonical correlation analysis) written in C++ and R. These building blocks are designed not only for direct use, but also as foundational components for developing new statistical methods that must operate on datasets too large to fit in memory. The package supports data provided either as HDF5 files or standard R objects, and is intended for high-dimensional applications such as omics and precision-medicine research.

r-blockr-dag 0.1.0
Propagated dependencies: r-shiny@1.11.1 r-jsonlite@2.0.0 r-htmltools@0.5.8.1 r-g6r@0.5.0 r-blockr-dock@0.1.0 r-blockr-core@0.1.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://bristolmyerssquibb.github.io/blockr.dag/
Licenses: GPL 3+
Build system: r
Synopsis: Directed Acyclic Graph Extension for 'blockr'
Description:

Building on the docking layout manager provided by blockr.dock', this provides an extension that allows for visualizing and manipulating a blockr board using a DAG-based user interface powered by the g6R graph visualisation HTML widget.

r-businessduration 0.2.0
Propagated dependencies: r-chron@2.3-62
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BusinessDuration
Licenses: AGPL 3
Build system: r
Synopsis: Calculates Business Duration Between Two Dates
Description:

Calculates business duration between two dates. This excluding weekends, public holidays and non-business hours.

r-bayesx 0.3-3
Propagated dependencies: r-sp@2.2-0 r-shapefiles@0.7.2 r-sf@1.0-23 r-interp@1.1-6 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: https://cran.r-project.org/package=BayesX
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: R Utilities Accompanying the Software Package BayesX
Description:

This package provides functions for exploring and visualising estimation results obtained with BayesX, a free software for estimating structured additive regression models (<https://www.uni-goettingen.de/de/bayesx/550513.html>). In addition, functions that allow to read, write and manipulate map objects that are required in spatial analyses performed with BayesX.

r-blr 1.6
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://cran.r-project.org/package=BLR
Licenses: GPL 2
Build system: r
Synopsis: Bayesian Linear Regression
Description:

Bayesian Linear Regression.

r-biogram 1.6.3
Propagated dependencies: r-slam@0.1-55 r-partitions@1.10-9 r-entropy@1.3.2 r-combinat@0.0-8
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: https://github.com/michbur/biogram
Licenses: GPL 3
Build system: r
Synopsis: N-Gram Analysis of Biological Sequences
Description:

This package provides tools for extraction and analysis of various n-grams (k-mers) derived from biological sequences (proteins or nucleic acids). Contains QuiPT (quick permutation test) for fast feature-filtering of the n-gram data.

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Total results: 68655