_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
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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-pymturkr 1.1.6
Propagated dependencies: r-xml@3.99-0.20 r-reticulate@1.44.1 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=pyMTurkR
Licenses: GPL 2
Build system: r
Synopsis: Client for the 'MTurk' Requester API
Description:

This package provides access to the latest Amazon Mechanical Turk ('MTurk') <https://www.mturk.com> Requester API (version 2017â 01â 17'), replacing the now deprecated MTurkR package.

r-prana 1.0.6
Propagated dependencies: r-robustbase@0.99-6 r-minet@3.68.0 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=PRANA
Licenses: GPL 3
Build system: r
Synopsis: Pseudo-Value Regression Approach for Network Analysis (PRANA)
Description:

This package provides a novel pseudo-value regression approach for the differential co-expression network analysis in expression data, which can incorporate additional clinical variables in the model. This is a direct regression modeling for the differential network analysis, and it is therefore computationally amenable for the most users. The full methodological details can be found in Ahn S et al (2023) <doi:10.1186/s12859-022-05123-w>.

r-pivotaltrackr 0.2.0
Propagated dependencies: r-httr@1.4.7 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://enpiar.com/r/pivotaltrackR/
Licenses: Expat
Build system: r
Synopsis: Client for the 'Pivotal Tracker' API
Description:

Pivotal Tracker <https://www.pivotaltracker.com> is a project management software-as-a-service that provides a REST API. This package provides an R interface to that API, allowing you to query it and work with its responses.

r-prevederer 0.0.1
Propagated dependencies: r-httr@1.4.7
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/wkdavis/prevederer
Licenses: Expat
Build system: r
Synopsis: Wrapper for the 'Prevedere' API
Description:

Easy and efficient access to the API provided by Prevedere', an industry insights and predictive analytics company. Query and download indicators, models and workbenches built with Prevedere for further analysis and reporting <https://www.prevedere.com/>.

r-pbsadmb 1.1.6
Propagated dependencies: r-pbsmodelling@2.70.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/pbs-software/pbs-admb
Licenses: GPL 2+
Build system: r
Synopsis: ADMB for R Using Scripts or GUI
Description:

This package provides a collection of software provides R support for ADMB (Automatic Differentiation Model Builder) and a GUI interface facilitates the conversion of ADMB template code to C code followed by compilation to a binary executable. Stand-alone functions can also be run by users not interested in clicking a GUI'.

r-pense 2.5.2
Propagated dependencies: r-testthat@3.3.0 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://dakep.github.io/pense-rpkg/
Licenses: Expat
Build system: r
Synopsis: Penalized Elastic Net S/MM-Estimator of Regression
Description:

Robust penalized (adaptive) elastic net S and M estimators for linear regression. The adaptive methods are proposed in Kepplinger, D. (2023) <doi:10.1016/j.csda.2023.107730> and the non-adaptive methods in Cohen Freue, G. V., Kepplinger, D., Salibián-Barrera, M., and Smucler, E. (2019) <doi:10.1214/19-AOAS1269>. The package implements robust hyper-parameter selection with robust information sharing cross-validation according to Kepplinger & Wei (2025) <doi:10.1080/00401706.2025.2540970>.

r-pvbcorrect 0.3.1
Propagated dependencies: r-mice@3.18.0 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/wnarifin/PVBcorrect/
Licenses: Expat
Build system: r
Synopsis: Partial Verification Bias Correction for Diagnostic Accuracy
Description:

This package performs partial verification bias (PVB) correction for binary diagnostic tests, where PVB arises from selective patient verification in diagnostic accuracy studies. Supports correction of important accuracy measures -- sensitivity, specificity, positive predictive values and negative predictive value -- under missing-at-random and missing-not-at-random missing data mechanisms. Available methods and references are "Begg and Greenes methods" in Alonzo & Pepe (2005) <doi:10.1111/j.1467-9876.2005.00477.x> and deGroot et al. (2011) <doi:10.1016/j.annepidem.2010.10.004>; "Multiple imputation" in Harel & Zhou (2006) <doi:10.1002/sim.2494>, "EM-based logistic regression" in Kosinski & Barnhart (2003) <doi:10.1111/1541-0420.00019>; "Inverse probability weighting" in Alonzo & Pepe (2005) <doi:10.1111/j.1467-9876.2005.00477.x>; "Inverse probability bootstrap sampling" in Nahorniak et al. (2015) <doi:10.1371/journal.pone.0131765> and Arifin & Yusof (2022) <doi:10.3390/diagnostics12112839>; "Scaled inverse probability resampling methods" in Arifin & Yusof (2025) <doi:10.1371/journal.pone.0321440>.

r-ppsbm 1.0.0
Propagated dependencies: r-rfast@2.1.5.2 r-gtools@3.9.5 r-clue@0.3-66
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org
Licenses: GPL 2+
Build system: r
Synopsis: Clustering in Longitudinal Networks
Description:

Stochastic block model used for dynamic graphs represented by Poisson processes. To model recurrent interaction events in continuous time, an extension of the stochastic block model is proposed where every individual belongs to a latent group and interactions between two individuals follow a conditional inhomogeneous Poisson process with intensity driven by the individualsâ latent groups. The model is shown to be identifiable and its estimation is based on a semiparametric variational expectation-maximization algorithm. Two versions of the method are developed, using either a nonparametric histogram approach (with an adaptive choice of the partition size) or kernel intensity estimators. The number of latent groups can be selected by an integrated classification likelihood criterion. Y. Baraud and L. Birgé (2009). <doi:10.1007/s00440-007-0126-6>. C. Biernacki, G. Celeux and G. Govaert (2000). <doi:10.1109/34.865189>. M. Corneli, P. Latouche and F. Rossi (2016). <doi:10.1016/j.neucom.2016.02.031>. J.-J. Daudin, F. Picard and S. Robin (2008). <doi:10.1007/s11222-007-9046-7>. A. P. Dempster, N. M. Laird and D. B. Rubin (1977). <http://www.jstor.org/stable/2984875>. G. Grégoire (1993). <http://www.jstor.org/stable/4616289>. L. Hubert and P. Arabie (1985). <doi:10.1007/BF01908075>. M. Jordan, Z. Ghahramani, T. Jaakkola and L. Saul (1999). <doi:10.1023/A:1007665907178>. C. Matias, T. Rebafka and F. Villers (2018). <doi:10.1093/biomet/asy016>. C. Matias and S. Robin (2014). <doi:10.1051/proc/201447004>. H. Ramlau-Hansen (1983). <doi:10.1214/aos/1176346152>. P. Reynaud-Bouret (2006). <doi:10.3150/bj/1155735930>.

r-phenology 2025.11.12
Propagated dependencies: r-optimx@2025-4.9 r-numderiv@2016.8-1.1 r-helpersmg@2025.12.22
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=phenology
Licenses: GPL 2
Build system: r
Synopsis: Tools to Manage a Parametric Function that Describes Phenology and More
Description:

This package provides functions used to fit and test the phenology of species based on counts. Based on Girondot, M. (2010) <doi:10.3354/esr00292> for the phenology function, Girondot, M. (2017) <doi:10.1016/j.ecolind.2017.05.063> for the convolution of negative binomial, Girondot, M. and Rizzo, A. (2015) <doi:10.2993/etbi-35-02-337-353.1> for Bayesian estimate, Pfaller JB, ..., Girondot M (2019) <doi:10.1007/s00227-019-3545-x> for tag-loss estimate, Hancock J, ..., Girondot M (2019) <doi:10.1016/j.ecolmodel.2019.04.013> for nesting history, Laloe J-O, ..., Girondot M, Hays GC (2020) <doi:10.1007/s00227-020-03686-x> for aggregating several seasons.

r-projectlsa 0.0.8
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-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@1.6.0.2 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-parsel 0.3.0
Propagated dependencies: r-rselenium@1.7.9 r-rlang@1.1.6 r-purrr@1.2.0 r-lubridate@1.9.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/till-tietz/parsel
Licenses: Expat
Build system: r
Synopsis: Parallel Dynamic Web-Scraping Using 'RSelenium'
Description:

This package provides a system to increase the efficiency of dynamic web-scraping with RSelenium by leveraging parallel processing. You provide a function wrapper for your RSelenium scraping routine with a set of inputs, and parsel runs it in several browser instances. Chunked input processing as well as error catching and logging ensures seamless execution and minimal data loss, even when unforeseen RSelenium errors occur. You can additionally build safe scraping functions with minimal coding by utilizing constructor functions that act as wrappers around RSelenium methods.

r-parquetize 0.5.8
Propagated dependencies: r-tidyselect@1.2.1 r-tibble@3.3.0 r-rsqlite@2.4.4 r-rlang@1.1.6 r-readr@2.1.6 r-lifecycle@1.0.4 r-jsonlite@2.0.0 r-haven@2.5.5 r-glue@1.8.0 r-fst@0.9.8 r-dplyr@1.1.4 r-dbi@1.2.3 r-curl@7.0.0 r-cli@3.6.5 r-arrow@22.0.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://ddotta.github.io/parquetize/
Licenses: ASL 2.0
Build system: r
Synopsis: Convert Files to Parquet Format
Description:

Collection of functions to get files in parquet format. Parquet is a columnar storage file format <https://parquet.apache.org/>. The files to convert can be of several formats ("csv", "RData", "rds", "RSQLite", "json", "ndjson", "SAS", "SPSS"...).

r-provtracer 1.0
Propagated dependencies: r-provparser@1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/End-to-end-provenance
Licenses: GPL 3
Build system: r
Synopsis: Uses Provenance to Trace File Lineage for One or more R Scripts
Description:

Uses provenance collected by rdtLite package or comparable tool to display information about input files, output files, and exchanged files for a single R script or a series of R scripts.

r-pumilior 1.3.1
Propagated dependencies: r-xml@3.99-0.20 r-rcurl@1.98-1.17
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: http://ljvillanueva.github.io/pumilioR/
Licenses: GPL 3
Build system: r
Synopsis: Pumilio in R
Description:

R package to query and get data out of a Pumilio sound archive system (http://ljvillanueva.github.io/pumilio/).

r-powermediation 0.3.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=powerMediation
Licenses: GPL 2+
Build system: r
Synopsis: Power/Sample Size Calculation for Mediation Analysis
Description:

This package provides functions to calculate power and sample size for testing (1) mediation effects; (2) the slope in a simple linear regression; (3) odds ratio in a simple logistic regression; (4) mean change for longitudinal study with 2 time points; (5) interaction effect in 2-way ANOVA; and (6) the slope in a simple Poisson regression.

r-palette 0.0.3
Propagated dependencies: r-vctrs@0.6.5 r-pillar@1.11.1 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/christopherkenny/palette
Licenses: Expat
Build system: r
Synopsis: Color Scheme Helpers
Description:

Hexadecimal codes are typically used to represent colors in R. Connecting these codes to their colors requires practice or memorization. palette provides a vctrs class for working with color palettes, including printing and plotting functions. The goal of the class is to place visual representations of color palettes directly on or, at least, next to their corresponding character representations. Palette extensions also are provided for data frames using pillar'.

r-ptable 1.0.0
Propagated dependencies: r-rmarkdown@2.30 r-rlang@1.1.6 r-rcolorbrewer@1.1-3 r-nloptr@2.2.1 r-ggplot2@4.0.1 r-flexdashboard@0.6.2 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/sdcTools/ptable
Licenses: FSDG-compatible
Build system: r
Synopsis: Generation of Perturbation Tables for the Cell-Key Method
Description:

Tabular data from statistical institutes and agencies are mostly confidential and must be protected prior to publications. The cell-key method is a post-tabular Statistical Disclosure Control perturbation technique that adds random noise to tabular data. The statistical properties of the perturbations are defined by some noise probability distributions - also referred to as perturbation tables. This tool can be used to create the perturbation tables based on a maximum entropy approach as described for example in Giessing (2016) <doi:10.1007/978-3-319-45381-1_18>. The perturbation tables created can finally be used to apply a cell-key method to frequency count or magnitude tables.

r-pie 1.0.0
Propagated dependencies: r-xgboost@1.7.11.1 r-gglasso@1.6
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PIE
Licenses: GPL 2
Build system: r
Synopsis: Partially Interpretable Model with Black-Box Refinement
Description:

This package implements a novel predictive model, Partially Interpretable Estimators (PIE), which jointly trains an interpretable model and a black-box model to achieve high predictive performance as well as partial model. See the paper, Wang, Yang, Li, and Wang (2021) <doi:10.48550/arXiv.2105.02410>.

r-pcovr 2.7.2
Propagated dependencies: r-threeway@1.1.4 r-matrix@1.7-4 r-mass@7.3-65 r-gparotation@2025.3-1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PCovR
Licenses: GPL 2+
Build system: r
Synopsis: Principal Covariates Regression
Description:

Analyzing regression data with many and/or highly collinear predictor variables, by simultaneously reducing the predictor variables to a limited number of components and regressing the criterion variables on these components (de Jong S. & Kiers H. A. L. (1992) <doi:10.1016/0169-7439(92)80100-I>). Several rotation and model selection options are provided.

r-pairsd3 0.1.3
Propagated dependencies: r-shiny@1.11.1 r-htmlwidgets@1.6.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/garthtarr/pairsD3/
Licenses: GPL 3+
Build system: r
Synopsis: D3 Scatterplot Matrices
Description:

This package creates an interactive scatterplot matrix using the D3 JavaScript library. See <https://d3js.org/> for more information on D3.

r-phenofit 0.3.11
Propagated dependencies: r-zoo@1.8-14 r-zeallot@0.2.0 r-ucminf@1.2.2 r-stringr@1.6.0 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-purrr@1.2.0 r-optimx@2025-4.9 r-numderiv@2016.8-1.1 r-magrittr@2.0.4 r-lubridate@1.9.4 r-gridextra@2.3 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/eco-hydro/phenofit
Licenses: GPL 2 FSDG-compatible
Build system: r
Synopsis: Extract Remote Sensing Vegetation Phenology
Description:

The merits of TIMESAT and phenopix are adopted. Besides, a simple and growing season dividing method and a practical snow elimination method based on Whittaker were proposed. 7 curve fitting methods and 4 phenology extraction methods were provided. Parameters boundary are considered for every curve fitting methods according to their ecological meaning. And optimx is used to select best optimization method for different curve fitting methods. Reference: Kong, D., (2020). R package: A state-of-the-art Vegetation Phenology extraction package, phenofit version 0.3.1, <doi:10.5281/zenodo.5150204>; Kong, D., Zhang, Y., Wang, D., Chen, J., & Gu, X. (2020). Photoperiod Explains the Asynchronization Between Vegetation Carbon Phenology and Vegetation Greenness Phenology. Journal of Geophysical Research: Biogeosciences, 125(8), e2020JG005636. <doi:10.1029/2020JG005636>; Kong, D., Zhang, Y., Gu, X., & Wang, D. (2019). A robust method for reconstructing global MODIS EVI time series on the Google Earth Engine. ISPRS Journal of Photogrammetry and Remote Sensing, 155, 13â 24; Zhang, Q., Kong, D., Shi, P., Singh, V.P., Sun, P., 2018. Vegetation phenology on the Qinghai-Tibetan Plateau and its response to climate change (1982â 2013). Agric. For. Meteorol. 248, 408â 417. <doi:10.1016/j.agrformet.2017.10.026>.

r-pubmedtk 1.0.4
Propagated dependencies: r-xml2@1.5.0 r-stringr@1.6.0 r-rlang@1.1.6 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-dplyr@1.1.4 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/bgcarlisle/pubmedtk
Licenses: AGPL 3+
Build system: r
Synopsis: 'Pubmed' Toolkit
Description:

This package provides various functions for retrieving and interpreting information from Pubmed via the API, <https://www.ncbi.nlm.nih.gov/home/develop/api/>.

r-pss-health 1.1.5
Propagated dependencies: r-writexl@1.5.4 r-shinyhelper@0.3.2 r-shinyfeedback@0.4.0 r-shinycssloaders@1.1.0 r-shiny@1.11.1 r-pwr2@1.0 r-pwr@1.3-0 r-proc@1.19.0.1 r-presize@0.3.9 r-powersurvepi@0.1.5 r-powermediation@0.3.4 r-plotly@4.11.0 r-longpower@1.0.27 r-kappasize@1.2 r-icc-sample-size@1.0 r-ggplot2@4.0.1 r-epir@2.0.90 r-envstats@3.1.0 r-easypower@1.0.2 r-dt@0.34.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://hcpa-unidade-bioestatistica.shinyapps.io/PSS_Health/
Licenses: GPL 2+
Build system: r
Synopsis: Power and Sample Size for Health Researchers via Shiny
Description:

Power and Sample Size for Health Researchers is a Shiny application that brings together a series of functions related to sample size and power calculations for common analysis in the healthcare field. There are functionalities to calculate the power, sample size to estimate or test hypotheses for means and proportions (including test for correlated groups, equivalence, non-inferiority and superiority), association, correlations coefficients, regression coefficients (linear, logistic, gamma, and Cox), linear mixed model, Cronbach's alpha, interobserver agreement, intraclass correlation coefficients, limit of agreement on Bland-Altman plots, area under the curve, sensitivity and specificity incorporating the prevalence of disease. You can also use the online version at <https://hcpa-unidade-bioestatistica.shinyapps.io/PSS_Health/>.

r-persomicsarray 1.0
Propagated dependencies: r-tiff@0.1-12 r-stringr@1.6.0 r-raster@3.6-32 r-jpeg@0.1-11
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PersomicsArray
Licenses: GPL 3
Build system: r
Synopsis: Automated Persomics Array Image Extraction
Description:

Automated identification of printed array positions from high content microscopy images and the export of those positions as individual images written to output as multi-layered tiff files.

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Total results: 21283