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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-pastboon 0.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pastboon
Licenses: Artistic License 2.0
Build system: r
Synopsis: Simulation of Parameterized Stochastic Boolean Networks
Description:

This package provides a Boolean network is a particular kind of discrete dynamical system where the variables are simple binary switches. Despite its simplicity, Boolean network modeling has been a successful method to describe the behavioral pattern of various phenomena. Applying stochastic noise to Boolean networks is a useful approach for representing the effects of various perturbing stimuli on complex systems. A number of methods have been developed to control noise effects on Boolean networks using parameters integrated into the update rules. This package provides functions to examine three such methods: Boolean network with perturbations (BNp), described by Trairatphisan et al. (2013) <doi:10.1186/1478-811X-11-46>, stochastic discrete dynamical systems (SDDS), proposed by Murrugarra et al. (2012) <doi:10.1186/1687-4153-2012-5>, and Boolean network with probabilistic edge weights (PEW), presented by Deritei et al. (2022) <doi:10.1371/journal.pcbi.1010536>. This package includes source code derived from the BoolNet package, which is licensed under the Artistic License 2.0.

r-pv3rs 1.0.0
Propagated dependencies: r-rcolorbrewer@1.1-3 r-purrr@1.2.0 r-partitions@1.10-9 r-multicool@1.0.1 r-matrixstats@1.5.0 r-igraph@2.2.1 r-fields@17.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://aimeertaylor.github.io/Pv3Rs/
Licenses: GPL 3+
Build system: r
Synopsis: Estimate the Cause of Recurrent Vivax Malaria using Genetic Data
Description:

Plot malaria parasite genetic data on two or more episodes. Compute per-person posterior probabilities that each Plasmodium vivax (Pv) recurrence is a recrudescence, relapse, or reinfection (3Rs) using per-person P. vivax genetic data on two or more episodes and a statistical model described in Taylor, Foo and White (2022) <doi:10.1101/2022.11.23.22282669>. Plot per-recurrence posterior probabilities.

r-proclhmm 1.0.1
Propagated dependencies: r-statmod@1.5.1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=proclhmm
Licenses: GPL 3+
Build system: r
Synopsis: Latent Hidden Markov Models for Response Process Data
Description:

This package provides functions for simulating from and fitting the latent hidden Markov models for response process data (Tang, 2024) <doi:10.1007/s11336-023-09938-1>. It also includes functions for simulating from and fitting ordinary hidden Markov models.

r-plotsemm 2.4
Propagated dependencies: r-shiny@1.11.1 r-rcpp@1.1.0 r-plyr@1.8.9 r-plotrix@3.8-13 r-mplusautomation@1.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/philchalmers/plotSEMM
Licenses: GPL 2+
Build system: r
Synopsis: Graphing Nonlinear Relations Among Latent Variables from Structural Equation Mixture Models
Description:

This package contains a graphical user interface to generate the diagnostic plots proposed by Bauer (2005; <doi:10.1207/s15328007sem1204_1>), Pek & Chalmers (2015; <doi:10.1080/10705511.2014.937790>), and Pek, Chalmers, R. Kok, & Losardo (2015; <doi:10.3102/1076998615589129>) to investigate nonlinear bivariate relationships in latent regression models using structural equation mixture models (SEMMs).

r-pch 2.2
Propagated dependencies: r-survival@3.8-3 r-hmisc@5.2-4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pch
Licenses: GPL 2
Build system: r
Synopsis: Piecewise Constant Hazard Models for Censored and Truncated Data
Description:

Piecewise constant hazard models for survival data. The package allows for right-censored, left-truncated, and interval-censored data.

r-pmlbr 0.3.0
Propagated dependencies: r-fnn@1.1.4.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/EpistasisLab/pmlbr
Licenses: GPL 2 FSDG-compatible
Build system: r
Synopsis: Interface to the Penn Machine Learning Benchmarks Data Repository
Description:

Check available classification and regression data sets from the PMLB repository and download them. The PMLB repository (<https://github.com/EpistasisLab/pmlbr>) contains a curated collection of data sets for evaluating and comparing machine learning algorithms. These data sets cover a range of applications, and include binary/multi-class classification problems and regression problems, as well as combinations of categorical, ordinal, and continuous features. There are currently over 150 datasets included in the PMLB repository.

r-pbir 0.1-0
Propagated dependencies: r-survival@3.8-3 r-cmprsk@2.2-12
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PBIR
Licenses: GPL 2+
Build system: r
Synopsis: Estimating the Probability of Being in Response and Related Outcomes
Description:

Make statistical inference on the probability of being in response, the duration of response, and the cumulative response rate up to a given time point. The method can be applied to analyze phase II randomized clinical trials with the endpoints being time to treatment response and time to progression or death.

r-plnmodels 1.2.2
Propagated dependencies: r-torch@0.16.3 r-tidyr@1.3.1 r-scales@1.4.0 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-r6@2.6.1 r-purrr@1.2.0 r-pscl@1.5.9 r-nloptr@2.2.1 r-matrix@1.7-4 r-mass@7.3-65 r-magrittr@2.0.4 r-igraph@2.2.1 r-gridextra@2.3 r-glassofast@1.0.1 r-ggplot2@4.0.1 r-future-apply@1.20.0 r-future@1.68.0 r-dplyr@1.1.4 r-corrplot@0.95 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://pln-team.github.io/PLNmodels/
Licenses: GPL 3+
Build system: r
Synopsis: Poisson Lognormal Models
Description:

The Poisson-lognormal model and variants (Chiquet, Mariadassou and Robin, 2021 <doi:10.3389/fevo.2021.588292>) can be used for a variety of multivariate problems when count data are at play, including principal component analysis for count data, discriminant analysis, model-based clustering and network inference. Implements variational algorithms to fit such models accompanied with a set of functions for visualization and diagnostic.

r-presenter 0.1.2
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-stringi@1.8.7 r-rvg@0.4.0 r-rlang@1.1.6 r-randomcolor@1.1.0.1 r-purrr@1.2.0 r-openxlsx@4.2.8.1 r-officer@0.7.1 r-magrittr@2.0.4 r-lubridate@1.9.4 r-janitor@2.2.1 r-framecleaner@0.2.1 r-formattable@0.2.1 r-flextable@0.9.10 r-dplyr@1.1.4 r-berryfunctions@1.22.13
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/Harrison4192/presenter
Licenses: Expat
Build system: r
Synopsis: Present Data with Style
Description:

Consists of custom wrapper functions using packages openxlsx', flextable', and officer to create highly formatted MS office friendly output of your data frames. These viewer friendly outputs are intended to match expectations of professional looking presentations in business and consulting scenarios. The functions are opinionated in the sense that they expect the input data frame to have certain properties in order to take advantage of the automated formatting.

r-prithulib 1.0.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=prithulib
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Perform Random Experiments
Description:

Enables user to perform the following: 1. Roll n number of die/dice (roll()). 2. Toss n number of coin(s) (toss()). 3. Play the game of Rock, Paper, Scissors. 4. Choose n number of card(s) from a pack of 52 playing cards (Joker optional).

r-projectlsa 0.0.7
Propagated dependencies: r-viridislite@0.4.2 r-tidyverse@2.0.0 r-tidyr@1.3.1 r-tidylpa@1.1.0 r-tibble@3.3.0 r-stringr@1.6.0 r-shinywidgets@0.9.0 r-shiny@1.11.1 r-semtools@0.5-7 r-semptools@0.3.2 r-semplot@1.1.7 r-rlang@1.1.6 r-readxl@1.4.5 r-readr@2.1.6 r-purrr@1.2.0 r-psych@2.5.6 r-polca@1.6.0.1 r-plotly@4.11.0 r-mirt@1.45.1 r-mclust@6.1.2 r-lavaan@0.6-20 r-haven@2.5.5 r-glca@1.4.2 r-ggplot2@4.0.1 r-ggiraph@0.9.2 r-dt@0.34.0 r-dplyr@1.1.4 r-data-table@1.17.8 r-colourpicker@1.3.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/hdmeasure/projectLSA
Licenses: Expat
Build system: r
Synopsis: Shiny Application for Latent Structure Analysis with a Graphical User Interface
Description:

This package provides an interactive Shiny-based toolkit for conducting latent structure analyses, including Latent Profile Analysis (LPA), Latent Class Analysis (LCA), Latent Trait Analysis (LTA/IRT), Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM). The implementation is grounded in established methodological frameworks: LPA is supported through tidyLPA (Rosenberg et al., 2018) <doi:10.21105/joss.00978>, LCA through poLCA (Linzer & Lewis, 2011) <doi:10.32614/CRAN.package.poLCA> & glca (Kim & Kim, 2024) <doi:10.32614/CRAN.package.glca>, LTA/IRT via mirt (Chalmers, 2012) <doi:10.18637/jss.v048.i06>, and EFA via psych (Revelle, 2025). SEM and CFA functionalities build upon the lavaan framework (Rosseel, 2012) <doi:10.18637/jss.v048.i02>. Users can upload datasets or use built-in examples, fit models, compare fit indices, visualize results, and export outputs without programming.

r-pubmedmining 1.0.0
Propagated dependencies: r-stringr@1.6.0 r-easypubmed@3.1.6
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PubMedMining
Licenses: Expat
Build system: r
Synopsis: Text-Mining of the 'PubMed' Repository
Description:

Easy function for text-mining the PubMed repository based on defined sets of terms. The relationship between fix-terms (related to your research topic) and pub-terms (terms which pivot around your research focus) is calculated using the pointwise mutual information algorithm ('PMI'). Church, Kenneth Ward and Hanks, Patrick (1990) <https://www.aclweb.org/anthology/J90-1003/> A text file is generated with the PMI'-scores for each fix-term. Then for each collocation pairs (a fix-term + a pub-term), a text file is generated with related article titles and publishing years. Additional Author section will follow in the next version updates.

r-pmxcode 0.3.1
Propagated dependencies: r-xfun@0.54 r-tidyr@1.3.1 r-shinyjs@2.1.0 r-shinyfiles@0.9.3 r-shinybs@0.61.1 r-shinyace@0.4.4 r-shiny@1.11.1 r-rlang@1.1.6 r-rhandsontable@0.3.8 r-readr@2.1.6 r-rclipboard@0.2.1 r-pillar@1.11.1 r-officer@0.7.1 r-markdown@2.0 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-htmlwidgets@1.6.4 r-htmltools@0.5.8.1 r-golem@0.5.1 r-glue@1.8.0 r-flextable@0.9.10 r-dplyr@1.1.4 r-config@0.3.2 r-bslib@0.9.0 r-bsicons@0.1.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/sbihorel/pmxcode
Licenses: Expat
Build system: r
Synopsis: Create Pharmacometric Models
Description:

This package provides a user interface to create or modify pharmacometric models for various modeling and simulation software platforms.

r-parsermd 0.2.0
Propagated dependencies: r-yaml@2.3.10 r-withr@3.0.2 r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-s7@0.2.1 r-rmarkdown@2.30 r-rlang@1.1.6 r-readr@2.1.6 r-rcpp@1.1.0 r-quarto@1.5.1 r-purrr@1.2.0 r-pillar@1.11.1 r-magrittr@2.0.4 r-fs@1.6.6 r-dplyr@1.1.4 r-cli@3.6.5 r-checkmate@2.3.3 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://rundel.github.io/parsermd/
Licenses: Expat
Build system: r
Synopsis: Formal Parser and Related Tools for R Markdown Documents
Description:

An implementation of a formal grammar and parser for R Markdown documents using the Boost Spirit X3 library. It also includes a collection of high level functions for working with the resulting abstract syntax tree.

r-pins 1.4.1
Propagated dependencies: r-yaml@2.3.10 r-withr@3.0.2 r-whisker@0.4.1 r-tibble@3.3.0 r-rlang@1.1.6 r-rappdirs@0.3.3 r-purrr@1.2.0 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-glue@1.8.0 r-generics@0.1.4 r-fs@1.6.6 r-digest@0.6.39 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://pins.rstudio.com/
Licenses: FSDG-compatible
Build system: r
Synopsis: Pin, Discover, and Share Resources
Description:

Publish data sets, models, and other R objects, making it easy to share them across projects and with your colleagues. You can pin objects to a variety of "boards", including local folders (to share on a networked drive or with DropBox'), Posit Connect', AWS S3', and more.

r-pafdr 1.0
Propagated dependencies: r-stringr@1.6.0 r-exams@2.4-3 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pafdR
Licenses: GPL 2
Build system: r
Synopsis: Book Companion for Processing and Analyzing Financial Data with R
Description:

This package provides access to material from the book "Processing and Analyzing Financial Data with R" by Marcelo Perlin (2017) available at <https://sites.google.com/view/pafdr/home>.

r-pcobw 0.0.1
Propagated dependencies: r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PCObw
Licenses: GPL 2+
Build system: r
Synopsis: Bandwidth Selector with Penalized Comparison to Overfitting Criterion
Description:

Bandwidth selector according to the Penalised Comparison to Overfitting (P.C.O.) criterion as described in Varet, S., Lacour, C., Massart, P., Rivoirard, V., (2019) <https://hal.archives-ouvertes.fr/hal-02002275>. It can be used with univariate and multivariate data.

r-partitionbefsp 1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=partitionBEFsp
Licenses: GPL 3
Build system: r
Synopsis: Methods for Calculating the Loreau & Hector 2001 BEF Partition
Description:

This package provides a collection of functions that can be used to estimate selection and complementarity effects, sensu Loreau & Hector (2001) <doi:10.1038/35083573>, even in cases where data are only available for a random subset of species (i.e. incomplete sample-level data). A full derivation and explanation of the statistical corrections used here is available in Clark et al. (2019) <doi:10.1111/2041-210X.13285>.

r-pipe-design 0.5.1
Propagated dependencies: r-xtable@1.8-4 r-gtools@3.9.5 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pipe.design
Licenses: GPL 2+
Build system: r
Synopsis: Dual-Agent Dose Escalation for Phase I Trials using the PIPE Design
Description:

This package implements the Product of Independent beta Probabilities dose Escalation (PIPE) design for dual-agent Phase I trials as described in Mander AP, Sweeting MJ (2015) <DOI:10.1002/sim.6434>.

r-protein8k 0.0.2
Propagated dependencies: r-shiny@1.11.1 r-rlang@1.1.6 r-rjson@0.2.23 r-magick@2.9.0 r-lattice@0.22-7 r-gridextra@2.3 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=protein8k
Licenses: CC0
Build system: r
Synopsis: Perform Analysis and Create Visualizations of Proteins
Description:

Read Protein Data Bank (PDB) files, performs its analysis, and presents the result using different visualization types including 3D. The package also has additional capability for handling Virus Report data from the National Center for Biotechnology Information (NCBI) database. Nature Structural Biology 10, 980 (2003) <doi:10.1038/nsb1203-980>. US National Library of Medicine (2021) <https://www.ncbi.nlm.nih.gov/datasets/docs/reference-docs/data-reports/virus/>.

r-prclust 1.3
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=prclust
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Penalized Regression-Based Clustering Method
Description:

Clustering is unsupervised and exploratory in nature. Yet, it can be performed through penalized regression with grouping pursuit. In this package, we provide two algorithms for fitting the penalized regression-based clustering (PRclust) with non-convex grouping penalties, such as group truncated lasso, MCP and SCAD. One algorithm is based on quadratic penalty and difference convex method. Another algorithm is based on difference convex and ADMM, called DC-ADD, which is more efficient. Generalized cross validation and stability based method were provided to select the tuning parameters. Rand index, adjusted Rand index and Jaccard index were provided to estimate the agreement between estimated cluster memberships and the truth.

r-poolvim 1.0.0
Propagated dependencies: r-ranger@0.17.0 r-hmisc@5.2-4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=poolVIM
Licenses: GPL 2+
Build system: r
Synopsis: Gene-Based Association Tests using the Actual Impurity Reduction (AIR) Variable Importance
Description:

Gene-based association tests using the actual impurity reduction (AIR) variable importance. The function aggregates AIR importance measures from a group of SNPs or probes and outputs a p-value for each gene. The procedures builds upon the method described in <doi:10.1093/Bioinformatics/Bty373> and will be published soon.

r-pointr 0.2.0
Propagated dependencies: r-stringr@1.6.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/jsugarelli/pointr/
Licenses: GPL 3
Build system: r
Synopsis: Working Comfortably with Pointers and Shortcuts to R Objects
Description:

R has no built-in pointer functionality. The pointr package fills this gap and lets you create pointers to R objects, including subsets of dataframes. This makes your R code more readable and maintainable.

r-pracpac 0.2.0
Propagated dependencies: r-rprojroot@2.1.1 r-renv@1.1.5 r-pkgbuild@1.4.8 r-magrittr@2.0.4 r-glue@1.8.0 r-fs@1.6.6
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://signaturescience.github.io/pracpac/
Licenses: Expat
Build system: r
Synopsis: Practical 'R' Packaging in 'Docker'
Description:

Streamline the creation of Docker images with R packages and dependencies embedded. The pracpac package provides a usethis'-like interface to creating Dockerfiles with dependencies managed by renv'. The pracpac functionality is described in Nagraj and Turner (2023) <doi:10.48550/arXiv.2303.07876>.

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