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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-posteriorbootstrap 0.1.2
Propagated dependencies: r-mass@7.3-65 r-e1071@1.7-16
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/alan-turing-institute/PosteriorBootstrap/
Licenses: Expat
Build system: r
Synopsis: Non-Parametric Sampling with Parallel Monte Carlo
Description:

An implementation of a non-parametric statistical model using a parallelised Monte Carlo sampling scheme. The method implemented in this package allows non-parametric inference to be regularized for small sample sizes, while also being more accurate than approximations such as variational Bayes. The concentration parameter is an effective sample size parameter, determining the faith we have in the model versus the data. When the concentration is low, the samples are close to the exact Bayesian logistic regression method; when the concentration is high, the samples are close to the simplified variational Bayes logistic regression. The method is described in full in the paper Lyddon, Walker, and Holmes (2018), "Nonparametric learning from Bayesian models with randomized objective functions" <arXiv:1806.11544>.

r-petersen 2025.3.1
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-spas@2025.2.1 r-rlang@1.1.6 r-reshape2@1.4.5 r-plyr@1.8.9 r-numderiv@2016.8-1.1 r-msm@1.8.2 r-matrix@1.7-4 r-mass@7.3-65 r-ggplot2@4.0.1 r-formula-tools@1.7.1 r-checkmate@2.3.3 r-btspas@2024.11.1 r-bbmle@1.0.25.1 r-aiccmodavg@2.3-4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/cschwarz-stat-sfu-ca/Petersen
Licenses: GPL 2
Build system: r
Synopsis: Estimators for Two-Sample Capture-Recapture Studies
Description:

This package provides a comprehensive implementation of Petersen-type estimators and its many variants for two-sample capture-recapture studies. A conditional likelihood approach is used that allows for tag loss; non reporting of tags; reward tags; categorical, geographical and temporal stratification; partial stratification; reverse capture-recapture; and continuous variables in modeling the probability of capture. Many examples from fisheries management are presented.

r-polycrossdesigns 1.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PolycrossDesigns
Licenses: GPL 2+
Build system: r
Synopsis: Polycross Designs ("PolycrossDesigns")
Description:

This package provides a polycross is the pollination by natural hybridization of a group of genotypes, generally selected, grown in isolation from other compatible genotypes in such a way to promote random open pollination. A particular practical application of the polycross method occurs in the production of a synthetic variety resulting from cross-pollinated plants. Laying out these experiments in appropriate designs, known as polycross designs, would not only save experimental resources but also gather more information from the experiment. Different experimental situations may arise in polycross nurseries which may be requiring different polycross designs (Varghese et. al. (2015) <doi:10.1080/02664763.2015.1043860>. " Experimental designs for open pollination in polycross trials"). This package contains a function named PD() which generates nine types of polycross designs suitable for various experimental situations.

r-ptwikiwords 0.0.3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/dfalbel/ptwikiwords
Licenses: Expat
Build system: r
Synopsis: Words Used in Portuguese Wikipedia
Description:

This package contains a dataset of words used in 15.000 randomly extracted pages from the Portuguese Wikipedia (<https://pt.wikipedia.org/>).

r-pbm 1.2.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/jonathanrd/pbm
Licenses: Expat
Build system: r
Synopsis: Protein Binding Models
Description:

Binding models which are useful when analysing protein-ligand interactions by techniques such as Biolayer Interferometry (BLI) or Surface Plasmon Resonance (SPR). Naman B. Shah, Thomas M. Duncan (2014) <doi:10.3791/51383>. Hoang H. Nguyen et al. (2015) <doi:10.3390/s150510481>. After initial binding parameters are known, binding curves can be simulated and parameters can be varied. The models within this package may also be used to fit a curve to measured binding data using non-linear regression.

r-pbbd 1.0.0
Propagated dependencies: r-ibd@1.6
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pbbd
Licenses: GPL 2+
Build system: r
Synopsis: Position Balanced and Nearly Position Balanced Block Designs
Description:

Generates a position balanced or nearly position balanced block design with given parameters. This package can also convert a given proper and equireplicate block design into a position balanced or nearly position balanced block design.

r-pack 0.1-2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pack
Licenses: GPL 3
Build system: r
Synopsis: Convert Values to/from Raw Vectors
Description:

This package provides functions to easily convert data to binary formats other programs/machines can understand.

r-probsamplingi 2.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=ProbSamplingI
Licenses: GPL 2+
Build system: r
Synopsis: Probabilistic Sampling Design and Strategies
Description:

It allows the user to determine sample sizes, select probabilistic samples, make estimates of different parameters for the total finite population and in studio domains, using the main design drawings.

r-prioriactions 0.5.0
Propagated dependencies: r-tidyr@1.3.1 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-proto@1.0.0 r-matrix@1.7-4 r-magrittr@2.0.4 r-dplyr@1.1.4 r-bh@1.87.0-1 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://prioriactions.github.io/prioriactions/
Licenses: GPL 2+
Build system: r
Synopsis: Multi-Action Conservation Planning
Description:

This uses a mixed integer mathematical programming (MIP) approach for building and solving multi-action planning problems, where the goal is to find an optimal combination of management actions that abate threats, in an efficient way while accounting for spatial aspects. Thus, optimizing the connectivity and conservation effectiveness of the prioritized units and of the deployed actions. The package is capable of handling different commercial (gurobi, CPLEX) and non-commercial (symphony, CBC) MIP solvers. Gurobi optimization solver can be installed using comprehensive instructions in the gurobi installation vignette of the prioritizr package (available in <https://prioritizr.net/articles/gurobi_installation_guide.html>). Instead, CPLEX optimization solver can be obtain from IBM CPLEX web page (available here <https://www.ibm.com/es-es/products/ilog-cplex-optimization-studio>). Additionally, the rcbc R package (available at <https://github.com/dirkschumacher/rcbc>) can be used to obtain solutions using the CBC optimization software (<https://github.com/coin-or/Cbc>). Methods used in the package refers to Salgado-Rojas et al. (2020) <doi:10.1016/j.ecolmodel.2019.108901>, Beyer et al. (2016) <doi:10.1016/j.ecolmodel.2016.02.005>, Cattarino et al. (2015) <doi:10.1371/journal.pone.0128027> and Watts et al. (2009) <doi:10.1016/j.envsoft.2009.06.005>. See the prioriactions website for more information, documentations and examples.

r-portalhacienda 0.1.7
Propagated dependencies: r-zoo@1.8-14 r-xts@0.14.1 r-timetk@2.9.1 r-tibble@3.3.0 r-purrr@1.2.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-httr@1.4.7 r-forecast@8.24.0 r-dplyr@1.1.4 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/fmgarciadiaz/PortalHacienda-CRAN
Licenses: GPL 3
Build system: r
Synopsis: Acceder Con R a Los Datos Del Portal De Hacienda
Description:

Obtener listado de datos, acceder y extender series del Portal de Datos de Hacienda.Las proyecciones se realizan con forecast', Hyndman RJ, Khandakar Y (2008) <doi:10.18637/jss.v027.i03>. Search, download and forecast time-series from the Ministry of Economy of Argentina. Forecasts are built with the forecast package, Hyndman RJ, Khandakar Y (2008) <doi:10.18637/jss.v027.i03>.

r-paper 1.0-6
Propagated dependencies: r-xtable@1.8-4 r-gmodels@2.19.1 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/hofnerb/papeR
Licenses: GPL 2
Build system: r
Synopsis: Toolbox for Writing Pretty Papers and Reports
Description:

This package provides a toolbox for writing knitr', Sweave or other LaTeX'- or markdown'-based reports and to prettify the output of various estimated models.

r-ppitables 0.6.1
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/katilingban/ppitables
Licenses: Expat
Build system: r
Synopsis: Lookup Tables to Generate Poverty Likelihoods and Rates using the Poverty Probability Index (PPI)
Description:

The Poverty Probability Index (PPI) is a poverty measurement tool for organizations and businesses with a mission to serve the poor. The PPI is statistically-sound, yet simple to use: the answers to 10 questions about a household's characteristics and asset ownership are scored to compute the likelihood that the household is living below the poverty line - or above by only a narrow margin. This package contains country-specific lookup data tables used as reference to determine the poverty likelihood of a household based on their score from the country-specific PPI questionnaire. These lookup tables have been extracted from documentation of the PPI found at <https://www.povertyindex.org> and managed by Innovations for Poverty Action <https://poverty-action.org/>.

r-projectmanagement 2.1.4
Propagated dependencies: r-tuvalues@1.1.0 r-triangle@1.0 r-plotly@4.11.0 r-lpsolveapi@5.5.2.0-17.14 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=ProjectManagement
Licenses: GPL 2+
Build system: r
Synopsis: Management of Deterministic and Stochastic Projects
Description:

Management problems of deterministic and stochastic projects. It obtains the duration of a project and the appropriate slack for each activity in a deterministic context. In addition it obtains a schedule of activities time (Castro, Gómez & Tejada (2007) <doi:10.1016/j.orl.2007.01.003>). It also allows the management of resources. When the project is done, and the actual duration for each activity is known, then it can know how long the project is delayed and make a fair delivery of the delay between each activity (Bergantiños, Valencia-Toledo & Vidal-Puga (2018) <doi:10.1016/j.dam.2017.08.012>). In a stochastic context it can estimate the average duration of the project and plot the density of this duration, as well as, the density of the early and last times of the chosen activities. As in the deterministic case, it can make a distribution of the delay generated by observing the project already carried out.

r-prqlr 0.10.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://prql.github.io/prqlc-r/
Licenses: Expat
Build system: r
Synopsis: R Bindings for the 'prqlc' Rust Library
Description:

This package provides a function to convert PRQL strings to SQL strings. Combined with other R functions that take SQL as an argument, PRQL can be used on R.

r-pencopulacond 0.2
Propagated dependencies: r-tsp@1.2.6 r-quadprog@1.5-8 r-pacotest@0.4.3 r-latticeextra@0.6-31 r-lattice@0.22-7 r-igraph@2.2.1 r-foreach@1.5.2 r-fda@6.3.0 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pencopulaCond
Licenses: GPL 2+
Build system: r
Synopsis: Estimating Non-Simplified Vine Copulas Using Penalized Splines
Description:

Estimating Non-Simplified Vine Copulas Using Penalized Splines.

r-pepmapviz 1.1.0
Propagated dependencies: r-stringr@1.6.0 r-shiny@1.11.1 r-rlang@1.1.6 r-ggplot2@4.0.1 r-ggnewscale@0.5.2 r-ggh4x@0.3.1 r-ggforce@0.5.0 r-dt@0.34.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PepMapViz
Licenses: Expat
Build system: r
Synopsis: Versatile Toolkit for Peptide Mapping, Visualization, and Comparative Exploration
Description:

This package provides a versatile R visualization package that empowers researchers with comprehensive visualization tools for seamlessly mapping peptides to protein sequences, identifying distinct domains and regions of interest, accentuating mutations, and highlighting post-translational modifications, all while enabling comparisons across diverse experimental conditions. Potential applications of PepMapViz include the visualization of cross-software mass spectrometry results at the peptide level for specific protein and domain details in a linearized format and post-translational modification coverage across different experimental conditions; unraveling insights into disease mechanisms. It also enables visualization of Major histocompatibility complex-presented peptide clusters in different antibody regions predicting immunogenicity in antibody drug development.

r-pdenaivebayes 0.2.9
Propagated dependencies: r-rcppparallel@5.1.11-1 r-rcpp@1.1.0 r-pracma@2.4.6 r-plotly@4.11.0 r-memshare@1.1.0 r-ggplot2@4.0.1 r-databionicswarm@2.0.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PDEnaiveBayes
Licenses: GPL 3
Build system: r
Synopsis: Plausible Naive Bayes Classifier Using PDE
Description:

This package provides a nonparametric, multicore-capable plausible naive Bayes classifier based on the Pareto density estimation (PDE) featuring a plausible approach to a pitfall in the Bayesian theorem covering low evidence cases. Stier, Q., Hoffmann, J., and Thrun, M.C.: "Classifying with the Fine Structure of Distributions: Leveraging Distributional Information for Robust and Plausible Naive Bayes" (2026), Machine Learning and Knowledge Extraction (MAKE), <DOI:10.3390/make8010013>.

r-profile 1.0.4
Propagated dependencies: r-withr@3.0.2 r-vctrs@0.6.5 r-tibble@3.3.0 r-rlang@1.1.6
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://r-prof.github.io/profile/
Licenses: Expat
Build system: r
Synopsis: Read, Manipulate, and Write Profiler Data
Description:

Defines a data structure for profiler data, and methods to read and write from the Rprof and pprof file formats.

r-poset 1.0.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://sites.google.com/view/lmaowisc/
Licenses: FSDG-compatible
Build system: r
Synopsis: Analysis of Partially Ordered Data
Description:

Win ratio approach to partially ordered data, such as multivariate ordinal responses under product (consensus) or prioritized order. Two-sample tests and multiplicative regression models are implemented (Mao, 2024, under revision).

r-putior 0.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://pjt222.github.io/putior/
Licenses: Expat
Build system: r
Synopsis: "Register In- and Outputs for Workflow Visualization"
Description:

This package provides tools for extracting and processing structured annotations from R and Python source files to facilitate workflow visualization. The package scans source files for special PUT annotations that define nodes, connections, and metadata within a data processing workflow. These annotations can then be used to generate visual representations of data flows and processing steps across polyglot software environments. Builds on concepts from literate programming Knuth (1984) <doi:10.1093/comjnl/27.2.97> and utilizes directed acyclic graph (DAG) theory for workflow representation Foraita, Spallek, and Zeeb (2014) <doi:10.1007/978-0-387-09834-0_65>. Diagram generation powered by Mermaid Sveidqvist (2014) <https://mermaid.js.org/>.

r-planetnicfi 1.0.5
Propagated dependencies: r-terra@1.8-86 r-sf@1.0-23 r-httr@1.4.7 r-glue@1.8.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/mlampros/PlanetNICFI
Licenses: GPL 3
Build system: r
Synopsis: Processing of the 'Planet NICFI' Satellite Imagery
Description:

It includes functions to download and process the Planet NICFI (Norway's International Climate and Forest Initiative) Satellite Imagery utilizing the Planet Mosaics API <https://developers.planet.com/docs/basemaps/reference/#tag/Basemaps-and-Mosaics>. GDAL (library for raster and vector geospatial data formats) and aria2c (paralleled download utility) must be installed and configured in the user's Operating System.

r-pomade 0.2.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-purrr@1.2.0 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-future@1.68.0 r-furrr@0.3.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://mikkelvembye.github.io/POMADE/
Licenses: Expat
Build system: r
Synopsis: Power for Meta-Analysis of Dependent Effects
Description:

This package provides functions to compute and plot power levels, minimum detectable effect sizes, and minimum required sample sizes for the test of the overall average effect size in meta-analysis of dependent effect sizes.

r-plnr 2025.11.22
Propagated dependencies: r-uuid@1.2-1 r-usethis@3.2.1 r-tidyr@1.3.1 r-r6@2.6.1 r-purrr@1.2.0 r-pbmcapply@1.5.1 r-glue@1.8.0 r-fs@1.6.6 r-foreach@1.5.2 r-digest@0.6.39 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://www.rwhite.no/plnr/
Licenses: Expat
Build system: r
Synopsis: Framework for Planning and Executing Analyses
Description:

This package provides a comprehensive framework for planning and executing analyses in R. It provides a structured approach to running the same function multiple times with different arguments, executing multiple functions on the same datasets, and creating systematic analyses across multiple strata or variables. The framework is particularly useful for applying the same analysis across multiple strata (e.g., locations, age groups), running statistical methods on multiple variables (e.g., exposures, outcomes), generating multiple tables or graphs for reports, and creating systematic surveillance analyses. Key features include efficient data management, structured analysis planning, flexible execution options, built-in debugging tools, and hash-based caching.

r-polycub 0.9.2
Propagated dependencies: r-sp@2.2-0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/bastistician/polyCub
Licenses: GPL 2
Build system: r
Synopsis: Cubature over Polygonal Domains
Description:

Numerical integration of continuously differentiable functions f(x,y) over simple closed polygonal domains. The following cubature methods are implemented: product Gauss cubature (Sommariva and Vianello, 2007, <doi:10.1007/s10543-007-0131-2>), the simple two-dimensional midpoint rule (wrapping spatstat.geom functions), and adaptive cubature for radially symmetric functions via line integrate() along the polygon boundary (Meyer and Held, 2014, <doi:10.1214/14-AOAS743>, Supplement B). For simple integration along the axes, the cubature package is more appropriate.

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