_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
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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-perk 0.0.9.2
Propagated dependencies: r-zoo@1.8-14 r-viridis@0.6.5 r-tidyr@1.3.1 r-tibble@3.3.0 r-shinywidgets@0.9.0 r-shinyjs@2.1.0 r-shiny@1.11.1 r-readr@2.1.6 r-plotly@4.11.0 r-magrittr@2.0.4 r-golem@0.5.1 r-ggplot2@4.0.1 r-forcats@1.0.1 r-dt@0.34.0 r-dplyr@1.1.4 r-config@0.3.2 r-colourpicker@1.3.0 r-bs4dash@2.3.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/jkkishore85/PERK/
Licenses: GPL 3+
Build system: r
Synopsis: Predicting Environmental Concentration and Risk
Description:

This package provides a Shiny Web Application to predict and visualize concentrations of pharmaceuticals in the aqueous environment. Jagadeesan K., Barden R. and Kasprzyk-Hordern B. (2022) <https://www.ssrn.com/abstract=4306129>.

r-panalysis 2.0
Propagated dependencies: r-ggplot2@4.0.1 r-coin@1.4-3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pAnalysis
Licenses: GPL 2
Build system: r
Synopsis: Benchmarking and Rescaling R2 using Noise Percentile Analysis
Description:

This package provides the tools needed to benchmark the R2 value corresponding to a certain acceptable noise level while also providing a rescaling function based on that noise level yielding a new value of R2 we refer to as R2k which is independent of both the number of degrees of freedom and the noise distribution function.

r-packetllm 0.1.1
Propagated dependencies: r-shinyjs@2.1.0 r-shiny@1.11.1 r-readtext@0.92.1 r-promises@1.5.0 r-pdftools@3.6.0 r-httr@1.4.7 r-future@1.68.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/AntoniCzolgowski/PacketLLM
Licenses: Expat
Build system: r
Synopsis: Interactive 'OpenAI' Model Integration in 'RStudio'
Description:

Offers an interactive RStudio gadget interface for communicating with OpenAI large language models (e.g., gpt-5', gpt-5-mini', gpt-5-nano') (<https://platform.openai.com/docs/api-reference>). Enables users to conduct multiple chat conversations simultaneously in separate tabs. Supports uploading local files (R, PDF, DOCX) to provide context for the models. Allows per-conversation configuration of system messages (where supported by the model). API interactions via the httr package are performed asynchronously using promises and future to avoid blocking the R console. Useful for tasks like code generation, text summarization, and document analysis directly within the RStudio environment. Requires an OpenAI API key set as an environment variable.

r-palm 1.1.6
Propagated dependencies: r-rcpp@1.1.0 r-r6@2.6.1 r-mvtnorm@1.3-3 r-minqa@1.2.8 r-gsl@2.1-9
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/b-steve/palm
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Fitting Point Process Models via the Palm Likelihood
Description:

This package provides functions to fit point process models using the Palm likelihood. First proposed by Tanaka, Ogata, and Stoyan (2008) <DOI:10.1002/bimj.200610339>, maximisation of the Palm likelihood can provide computationally efficient parameter estimation for point process models in situations where the full likelihood is intractable. This package is chiefly focused on Neyman-Scott point processes, but can also fit the void processes proposed by Jones-Todd et al. (2019) <DOI:10.1002/sim.8046>. The development of this package was motivated by the analysis of capture-recapture surveys on which individuals cannot be identified---the data from which can conceptually be seen as a clustered point process (Stevenson, Borchers, and Fewster, 2019 <DOI:10.1111/biom.12983>). As such, some of the functions in this package are specifically for the estimation of cetacean density from two-camera aerial surveys.

r-poppyramid 0.1.1
Propagated dependencies: r-tibble@3.3.0 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://github.com/musajajorge/popPyramid
Licenses: GPL 3
Build system: r
Synopsis: Population Pyramids
Description:

This package provides functions that facilitate the elaboration of population pyramids.

r-polypharmacy 1.0.0
Propagated dependencies: r-stringr@1.6.0 r-lubridate@1.9.4 r-itertools@0.1-3 r-foreach@1.5.2 r-doparallel@1.0.17 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=polypharmacy
Licenses: Expat
Build system: r
Synopsis: Calculate Several Polypharmacy Indicators
Description:

Analyse prescription drug deliveries to calculate several indicators of polypharmacy corresponding to the various definitions found in the literature. Bjerrum, L., Rosholm, J. U., Hallas, J., & Kragstrup, J. (1997) <doi:10.1007/s002280050329>. Chan, D.-C., Hao, Y.-T., & Wu, S.-C. (2009a) <doi:10.1002/pds.1712>. Fincke, B. G., Snyder, K., Cantillon, C., Gaehde, S., Standring, P., Fiore, L., ... Gagnon, D.R. (2005) <doi:10.1002/pds.966>. Hovstadius, B., Astrand, B., & Petersson, G. (2009) <doi:10.1186/1472-6904-9-11>. Hovstadius, B., Astrand, B., & Petersson, G. (2010) <doi:10.1002/pds.1921>. Kennerfalk, A., Ruigómez, A., Wallander, M.-A., Wilhelmsen, L., & Johansson, S. (2002) <doi:10.1345/aph.1A226>. Masnoon, N., Shakib, S., Kalisch-Ellett, L., & Caughey, G. E. (2017) <doi:10.1186/s12877-017-0621-2>. Narayan, S. W., & Nishtala, P. S. (2015) <doi:10.1007/s40801-015-0020-y>. Nishtala, P. S., & Salahudeen, M. S. (2015) <doi:10.1159/000368191>. Park, H. Y., Ryu, H. N., Shim, M. K., Sohn, H. S., & Kwon, J. W. (2016) <doi:10.5414/cp202484>. Veehof, L., Stewart, R., Haaijer-Ruskamp, F., & Jong, B. M. (2000) <doi:10.1093/fampra/17.3.261>.

r-pldamixture 0.1.1
Propagated dependencies: r-survival@3.8-3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/bpriy/pldamixture
Licenses: GPL 2
Build system: r
Synopsis: Post-Linkage Data Analysis Based on Mixture Modelling
Description:

Perform inference in the secondary analysis setting with linked data potentially containing mismatch errors. Only the linked data file may be accessible and information about the record linkage process may be limited or unavailable. Implements the General Framework for Regression with Mismatched Data developed by Slawski et al. (2023) <doi:10.48550/arXiv.2306.00909>. The framework uses a mixture model for pairs of linked records whose two components reflect distributions conditional on match status, i.e., correct match or mismatch. Inference is based on composite likelihood and the Expectation-Maximization (EM) algorithm. The package currently supports Cox Proportional Hazards Regression (right-censored data only) and Generalized Linear Regression Models (Gaussian, Gamma, Poisson, and Logistic (binary models only)). Information about the underlying record linkage process can be incorporated into the method if available (e.g., assumed overall mismatch rate, safe matches, predictors of match status, or predicted probabilities of correct matches).

r-pensim 1.3.6
Propagated dependencies: r-penalized@0.9-53 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://waldronlab.io/pensim/
Licenses: GPL 2+
Build system: r
Synopsis: Simulation of High-Dimensional Data and Parallelized Repeated Penalized Regression
Description:

Simulation of continuous, correlated high-dimensional data with time to event or binary response, and parallelized functions for Lasso, Ridge, and Elastic Net penalized regression with repeated starts and two-dimensional tuning of the Elastic Net.

r-probshiny 0.1.0
Propagated dependencies: r-shinymatrix@0.8.0 r-shiny@1.11.1 r-rpivottable@0.3.0 r-rmarkdown@2.30 r-laplacesdemon@16.1.6 r-epitools@0.5-10.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PROBShiny
Licenses: GPL 2
Build system: r
Synopsis: Interactive Document for Working with Basic Probability
Description:

An interactive document on the topic of basic probability using rmarkdown and shiny packages. Runtime examples are provided in the package function as well as at <https://analyticmodels.shinyapps.io/BayesShiny/>.

r-pk4adi 0.1.3.2
Propagated dependencies: r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://www.r-project.org
Licenses: Expat
Build system: r
Synopsis: PK for Anesthetic Depth Indicators
Description:

Calculate and compare the prediction probability (PK) values for Anesthetic Depth Indicators. The PK values are widely used for measuring the performance of anesthetic depth and were first proposed by the group of Dr. Warren D. Smith in the paper Warren D. Smith; Robert C. Dutton; Ty N. Smith (1996) <doi:10.1097/00000542-199601000-00005> and Warren D. Smith; Robert C. Dutton; Ty N. Smith (1996) <doi:10.1002/(SICI)1097-0258(19960615)15:11%3C1199::AID-SIM218%3E3.0.CO;2-Y>. The authors provided two Microsoft Excel files in xls format for calculating and comparing PK values. This package provides an easy-to-use API for calculating and comparing PK values in R.

r-pptreeviz 2.0.4
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-partykit@1.2-24 r-gridextra@2.3 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=PPtreeViz
Licenses: GPL 2+
Build system: r
Synopsis: Projection Pursuit Classification Tree Visualization
Description:

This package provides tools for exploring projection pursuit classification tree using various projection pursuit indexes.

r-piir 0.3.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=piiR
Licenses: Expat
Build system: r
Synopsis: Predictive Information Index ('PII')
Description:

This package provides a simple implementation of the Predictive Information Index ('PII').

r-pmapscore 0.1.1
Propagated dependencies: r-survminer@0.5.1 r-survival@3.8-3 r-proc@1.19.0.1 r-org-hs-eg-db@3.22.0 r-maftools@2.26.0 r-glmnet@4.1-10 r-clusterprofiler@4.18.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PMAPscore
Licenses: GPL 2+
Build system: r
Synopsis: Identify Prognosis-Related Pathways Altered by Somatic Mutation
Description:

We innovatively defined a pathway mutation accumulate perturbation score (PMAPscore) to reflect the position and the cumulative effect of the genetic mutations at the pathway level. Based on the PMAPscore of pathways, identified prognosis-related pathways altered by somatic mutation and predict immunotherapy efficacy by constructing a multiple-pathway-based risk model (Tarca, Adi Laurentiu et al (2008) <doi:10.1093/bioinformatics/btn577>).

r-pannotator 1.0.0.4
Propagated dependencies: r-stringr@1.6.0 r-shinywidgets@0.9.0 r-shinythemes@1.2.0 r-shinyjs@2.1.0 r-shinyhelper@0.3.2 r-shinyfiles@0.9.3 r-shiny@1.11.1 r-sf@1.0-23 r-scales@1.4.0 r-readr@2.1.6 r-magrittr@2.0.4 r-leafpm@0.1.0 r-leaflet-extras@2.0.1 r-leaflet@2.2.3 r-jsonlite@2.0.0 r-jsonify@1.2.3 r-jpeg@0.1-11 r-htmlwidgets@1.6.4 r-golem@0.5.1 r-ggplot2@4.0.1 r-geojsonsf@2.0.5 r-exiftoolr@0.2.8 r-dplyr@1.1.4 r-configr@0.3.5 r-config@0.3.2 r-colourpicker@1.3.0 r-bslib@0.9.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/NunzioKnerr/pannotator_package_source
Licenses: GPL 3+
Build system: r
Synopsis: Visualisation and Annotation of 360 Degree Imagery
Description:

This package provides a customisable R shiny app for immersively visualising, mapping and annotating panospheric (360 degree) imagery. The flexible interface allows annotation of any geocoded images using up to 4 user specified dropdown menus. The app uses leaflet to render maps that display the geo-locations of images and panellum <https://pannellum.org/>, a lightweight panorama viewer for the web, to render images in virtual 360 degree viewing mode. Key functions include the ability to draw on & export parts of 360 images for downstream applications. Users can also draw polygons and points on map imagery related to the panoramic images and export them for further analysis. Downstream applications include using annotations to train Artificial Intelligence/Machine Learning (AI/ML) models and geospatial modelling and analysis of camera based survey data.

r-pooltestr 0.2.0
Propagated dependencies: r-tibble@3.3.0 r-stringr@1.6.0 r-stanheaders@2.32.10 r-rstantools@2.5.0 r-rstan@2.32.7 r-rlang@1.1.6 r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-progress@1.2.3 r-lme4@1.1-37 r-dplyr@1.1.4 r-brms@2.23.0 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/AngusMcLure/PoolTestR
Licenses: GPL 3+
Build system: r
Synopsis: Prevalence and Regression for Pool-Tested (Group-Tested) Data
Description:

An easy-to-use tool for working with presence/absence tests on pooled or grouped samples. The primary application is for estimating prevalence of a marker in a population based on the results of tests on pooled specimens. This sampling method is often employed in surveillance of rare conditions in humans or animals (e.g. molecular xenomonitoring). The package was initially conceived as an R-based alternative to the molecular xenomonitoring software, PoolScreen <https://sites.uab.edu/statgenetics/software/>. However, it goes further, allowing for estimates of prevalence to be adjusted for hierarchical sampling frames, and perform flexible mixed-effect regression analyses (McLure et al. Environmental Modelling and Software. <DOI:10.1016/j.envsoft.2021.105158>). The package is currently in early stages, however more features are planned or in the works: e.g. adjustments for imperfect test specificity/sensitivity, functions for helping with optimal experimental design, and functions for spatial modelling.

r-processmonitr 0.1.0
Propagated dependencies: r-shiny@1.11.1 r-miniui@0.1.2 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-edear@1.0.0 r-dplyr@1.1.4 r-bupar@1.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://www.bupar.net
Licenses: Expat
Build system: r
Synopsis: Building Process Monitoring Dashboards
Description:

This package provides functions for constructing dashboards for business process monitoring. Building on the event log objects class from package bupaR'. Allows the use to assemble custom shiny dashboards based on process data.

r-prenoms 0.0.1
Propagated dependencies: r-tibble@3.3.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: <https://github.com/desautm/prenoms>
Licenses: Expat
Build system: r
Synopsis: Names Given to Babies in Quebec Between 1980 and 2020
Description:

This package provides a database containing the names of the babies born in Quebec between 1980 and 2020.

r-ppwdeming 2.0.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=ppwdeming
Licenses: GPL 3+
Build system: r
Synopsis: Precision Profile Weighted Deming Regression
Description:

Weighted Deming regression, also known as errors-in-variable regression, is applied with suitable weights. Weights are modeled via a precision profile; thus the methods implemented here are referred to as precision profile weighted Deming (PWD) regression. The package covers two settings â one where the precision profiles are known either from external studies or from adequate replication of the X and Y readings, and one in which there is a plausible functional form for the precision profiles but the exact (unknown) function must be estimated from the (generally singlicate) readings. The function set includes tools for: estimated standard errors (via jackknifing); standardized-residual analysis function with regression diagnostic tools for normality, linearity and constant variance; and an outlier analysis identifying significant outliers for closer investigation. The following reference provides further information on mathematical derivations and applications. Hawkins, D.M., and J.J. Kraker. Precision Profile Weighted Deming Regression for Methods Comparison', (in press) <doi:10.1093/jalm/jfaf183>.

r-plelma 0.2.2
Propagated dependencies: r-mlogit@1.1-3 r-dfidx@0.2-0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pleLMA
Licenses: GPL 3+
Build system: r
Synopsis: Pseudo-Likelihood Estimation of Log-Multiplicative Association Models
Description:

Log-multiplicative association models (LMA) are models for cross-classifications of categorical variables where interactions are represented by products of category scale values and an association parameter. Maximum likelihood estimation (MLE) fails for moderate to large numbers of categorical variables. The pleLMA package overcomes this limitation of MLE by using pseudo-likelihood estimation to fit the models to small or large cross-classifications dichotomous or multi-category variables. Originally proposed by Besag (1974, <doi:10.1111/j.2517-6161.1974.tb00999.x>), pseudo-likelihood estimation takes large complex models and breaks it down into smaller ones. Rather than maximizing the likelihood of the joint distribution of all the variables, a pseudo-likelihood function, which is the product likelihoods from conditional distributions, is maximized. LMA models can be derived from a number of different frameworks including (but not limited to) graphical models and uni-dimensional and multi-dimensional item response theory models. More details about the models and estimation can be found in the vignette.

r-pavo 2.9.0
Propagated dependencies: r-viridislite@0.4.2 r-sf@1.0-23 r-progressr@0.18.0 r-plot3d@1.4.2 r-magick@2.9.0 r-lightr@1.9.0 r-geometry@0.5.2 r-future-apply@1.20.0 r-farver@2.1.2 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: http://pavo.colrverse.com
Licenses: GPL 2+
Build system: r
Synopsis: Perceptual Analysis, Visualization and Organization of Spectral Colour Data
Description:

This package provides a cohesive framework for the spectral and spatial analysis of colour described in Maia, Eliason, Bitton, Doucet & Shawkey (2013) <doi:10.1111/2041-210X.12069> and Maia, Gruson, Endler & White (2019) <doi:10.1111/2041-210X.13174>.

r-pagfl 1.1.4
Propagated dependencies: r-rcppthread@2.2.0 r-rcppparallel@5.1.11-1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-lifecycle@1.0.4 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/Paul-Haimerl/PAGFL
Licenses: AGPL 3+
Build system: r
Synopsis: Joint Estimation of Latent Groups and Group-Specific Coefficients in (Time-Varying) Panel Data Models
Description:

Latent group structures are a common challenge in panel data analysis. Disregarding group-level heterogeneity can introduce bias. Conversely, estimating individual coefficients for each cross-sectional unit is inefficient and may lead to high uncertainty. This package addresses the issue of unobservable group structures by implementing the pairwise adaptive group fused Lasso (PAGFL) by Mehrabani (2023) <doi:10.1016/j.jeconom.2022.12.002>. PAGFL identifies latent group structures and group-specific coefficients in a single step. On top of that, we extend the PAGFL to time-varying coefficient functions (FUSE-TIME), following Haimerl et al. (2025) <doi:10.48550/arXiv.2503.23165>.

r-puls 0.1.3
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-purrr@1.2.0 r-monoclust@1.2.1 r-ggplot2@4.0.1 r-fda-usc@2.2.0 r-fda@6.3.0 r-dplyr@1.1.4 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://vinhtantran.github.io/puls/
Licenses: GPL 2+
Build system: r
Synopsis: Partitioning Using Local Subregions
Description:

This package provides a method of clustering functional data using subregion information of the curves. It is intended to supplement the fda and fda.usc packages in functional data object clustering. It also facilitates the printing and plotting of the results in a tree format and limits the partitioning candidates into a specific set of subregions.

r-pgee 1.5
Propagated dependencies: r-mvtnorm@1.3-3 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PGEE
Licenses: GPL 2+
Build system: r
Synopsis: Penalized Generalized Estimating Equations in High-Dimension
Description:

Fits penalized generalized estimating equations to longitudinal data with high-dimensional covariates.

r-profoc 1.3.4
Propagated dependencies: r-tibble@3.3.0 r-splines2@0.5.4 r-rcpptimer@1.2.1 r-rcppprogress@0.4.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-matrix@1.7-4 r-lifecycle@1.0.4 r-ggplot2@4.0.1 r-generics@0.1.4 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://profoc.berrisch.biz
Licenses: GPL 3+
Build system: r
Synopsis: Probabilistic Forecast Combination Using CRPS Learning
Description:

Combine probabilistic forecasts using CRPS learning algorithms proposed in Berrisch, Ziel (2021) <doi:10.48550/arXiv.2102.00968> <doi:10.1016/j.jeconom.2021.11.008>. The package implements multiple online learning algorithms like Bernstein online aggregation; see Wintenberger (2014) <doi:10.48550/arXiv.1404.1356>. Quantile regression is also implemented for comparison purposes. Model parameters can be tuned automatically with respect to the loss of the forecast combination. Methods like predict(), update(), plot() and print() are available for convenience. This package utilizes the optim C++ library for numeric optimization <https://github.com/kthohr/optim>.

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