_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/

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-plinkfile 0.2.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=plinkFile
Licenses: GPL 2+
Build system: r
Synopsis: 'PLINK' (and 'GCTA') File Helpers
Description:

Reads/write binary genotype file compatible with PLINK <https://www.cog-genomics.org/plink/1.9/input#bed> into/from a R matrix; traverse genotype data one windows of variants at a time, like apply() or a for loop; reads/writes genotype relatedness/kinship matrices created by PLINK <https://www.cog-genomics.org/plink/1.9/distance#make_rel> or GCTA <https://cnsgenomics.com/software/gcta/#MakingaGRM> into/from a R square matrix. It is best used for bringing data produced by PLINK and GCTA into R workflow.

r-preknitposthtmlrender 0.1.0
Propagated dependencies: r-xml@3.99-0.20 r-rmarkdown@2.30 r-knitr@1.50
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/chinsoon12/PreKnitPostHTMLRender
Licenses: GPL 2+ FSDG-compatible
Build system: r
Synopsis: Pre-Knitting Processing and Post HTML-Rendering Processing
Description:

Dynamize headers or R code within Rmd files to prevent proliferation of Rmd files for similar reports. Add in external HTML document within rmarkdown rendered HTML doc.

r-ppweibull 1.0
Propagated dependencies: r-survival@3.8-3 r-segmented@2.1-4 r-pracma@2.4.6 r-nloptr@2.2.1 r-msm@1.8.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=ppweibull
Licenses: GPL 2+
Build system: r
Synopsis: Piecewise Lifetime Models
Description:

This package provides functions for estimation and data generation for several piecewise lifetime distributions. The package implements the power piecewise Weibull model, which includes the piecewise Rayleigh and piecewise exponential models as special cases. See Feigl and Zelen (1965) <doi:10.2307/2528247> for methodological details.

r-presentes 0.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://diegokoz.github.io/presentes/
Licenses: Expat
Build system: r
Synopsis: Registry of Victims of State Terrorism in Argentina
Description:

Compilation and digitalization of the official registry of victims of state terrorism in Argentina during the last military coup. The original data comes from RUVTE-ILID (2019) <https://www.argentina.gob.ar/sitiosdememoria/ruvte/informe> and <http://basededatos.parquedelamemoria.org.ar/registros/>. The title, presentes, comes from present in spanish.

r-pscore 0.4.1
Propagated dependencies: r-reshape2@1.4.5 r-lavaan@0.6-20 r-jwileymisc@1.4.4 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://score-project.org
Licenses: LGPL 3
Build system: r
Synopsis: Standardizing Physiological Composite Risk Endpoints
Description:

This package provides a number of functions to simplify and automate the scoring, comparison, and evaluation of different ways of creating composites of data. It is particularly aimed at facilitating the creation of physiological composites of metabolic syndrome symptom score (MetSSS) and allostatic load (AL). Provides a wrapper to calculate the MetSSS on new data using the Healthy Hearts formula.

r-pareto 2.4.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/ulrichriegel/Pareto#pareto
Licenses: GPL 2+
Build system: r
Synopsis: The Pareto, Piecewise Pareto and Generalized Pareto Distribution
Description:

Utilities for the Pareto, piecewise Pareto and generalized Pareto distribution that are useful for reinsurance pricing. In particular, the package provides a non-trivial algorithm that can be used to match the expected losses of a tower of reinsurance layers with a layer-independent collective risk model. The theoretical background of the matching algorithm and most other methods are described in Ulrich Riegel (2018) <doi:10.1007/s13385-018-0177-3>.

r-patientprofiles 1.5.0
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-rlang@1.1.6 r-purrr@1.2.0 r-omopgenerics@1.3.7 r-lifecycle@1.0.4 r-dplyr@1.1.4 r-clock@0.7.3 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://darwin-eu.github.io/PatientProfiles/
Licenses: FSDG-compatible
Build system: r
Synopsis: Identify Characteristics of Patients in the OMOP Common Data Model
Description:

Identify the characteristics of patients in data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model.

r-previsionio 11.7.0
Propagated dependencies: r-xml@3.99-0.20 r-plotly@4.11.0 r-metrics@0.1.4 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-futile-logger@1.4.3 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=previsionio
Licenses: Expat
Build system: r
Synopsis: 'Prevision.io' R SDK
Description:

For working with the Prevision.io AI model management platform's API <https://prevision.io/>.

r-pandemonium 0.2.4
Propagated dependencies: r-viridis@0.6.5 r-uwot@0.2.4 r-tourr@1.2.6 r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-shinythemes@1.2.0 r-shinyfeedback@0.4.0 r-shiny@1.11.1 r-rtsne@0.17 r-rlang@1.1.6 r-rcolorbrewer@1.1-3 r-plotly@4.11.0 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-ggpcp@0.2.0 r-fpc@2.2-13 r-dt@0.34.0 r-dplyr@1.1.4 r-detourr@0.2.0 r-dendextend@1.19.1 r-crosstalk@1.2.2 r-alphahull@2.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://gabrielmccoy.github.io/pandemonium/
Licenses: Expat
Build system: r
Synopsis: High Dimensional Analysis in Linked Spaces
Description:

This package provides a shiny GUI that performs high dimensional cluster analysis. This tool performs data preparation, clustering and visualisation within a dynamic GUI. With interactive methods allowing the user to change settings all without having to to leave the GUI. An earlier version of this package was described in Laa and Valencia (2022) <doi:10.1140/epjp/s13360-021-02310-1>.

r-prioritizr 8.1.0
Propagated dependencies: r-withr@3.0.2 r-units@1.0-0 r-tibble@3.3.0 r-terra@1.8-86 r-sf@1.0-23 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-raster@3.6-32 r-r6@2.6.1 r-matrix@1.7-4 r-magrittr@2.0.4 r-igraph@2.2.1 r-exactextractr@0.10.0 r-cli@3.6.5 r-bh@1.87.0-1 r-assertthat@0.2.1 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://prioritizr.net
Licenses: GPL 3
Build system: r
Synopsis: Systematic Conservation Prioritization in R
Description:

Systematic conservation prioritization using mixed integer linear programming (MILP). It provides a flexible interface for building and solving conservation planning problems. Once built, conservation planning problems can be solved using a variety of commercial and open-source exact algorithm solvers. By using exact algorithm solvers, solutions can be generated that are guaranteed to be optimal (or within a pre-specified optimality gap). Furthermore, conservation problems can be constructed to optimize the spatial allocation of different management actions or zones, meaning that conservation practitioners can identify solutions that benefit multiple stakeholders. To solve large-scale or complex conservation planning problems, users should install the Gurobi optimization software (available from <https://www.gurobi.com/>) and the gurobi R package (see Gurobi Installation Guide vignette for details). Users can also install the IBM CPLEX software (<https://www.ibm.com/products/ilog-cplex-optimization-studio/cplex-optimizer>) and the cplexAPI R package (available at <https://github.com/cran/cplexAPI>). Additionally, the rcbc R package (available at <https://github.com/dirkschumacher/rcbc>) can be used to generate solutions using the CBC optimization software (<https://github.com/coin-or/Cbc>). For further details, see Hanson et al. (2025) <doi:10.1111/cobi.14376>.

r-phyloregion 1.0.9
Propagated dependencies: r-vegan@2.7-2 r-terra@1.8-86 r-smoothr@1.2.1 r-predicts@0.1-19 r-phangorn@2.12.1 r-matrix@1.7-4 r-maptpx@1.9-7 r-igraph@2.2.1 r-colorspace@2.1-2 r-clustmixtype@0.4-2 r-betapart@1.6.1 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/darunabas/phyloregion
Licenses: AGPL 3
Build system: r
Synopsis: Biogeographic Regionalization and Macroecology
Description:

Computational infrastructure for biogeography, community ecology, and biodiversity conservation (Daru et al. 2020) <doi:10.1111/2041-210X.13478>. It is based on the methods described in Daru et al. (2020) <doi:10.1038/s41467-020-15921-6>. The original conceptual work is described in Daru et al. (2017) <doi:10.1016/j.tree.2017.08.013> on patterns and processes of biogeographical regionalization. Additionally, the package contains fast and efficient functions to compute more standard conservation measures such as phylogenetic diversity, phylogenetic endemism, evolutionary distinctiveness and global endangerment, as well as compositional turnover (e.g., beta diversity).

r-probstats4econ 0.3.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://probstats4econ.com/package.html
Licenses: GPL 3+
Build system: r
Synopsis: Companion Package to Probability and Statistics for Economics and Business
Description:

Utilities for multiple hypothesis testing, companion datasets from "Probability and Statistics for Economics and Business: An Introduction Using R" by Jason Abrevaya (MIT Press, under contract).

r-prp 0.1.1
Propagated dependencies: r-mvtnorm@1.3-3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PRP
Licenses: GPL 2
Build system: r
Synopsis: Bayesian Prior and Posterior Predictive Replication Assessment
Description:

Utilize the Bayesian prior and posterior predictive checking approach to provide a statistical assessment of replication success and failure. The package is based on the methods proposed in Zhao,Y., Wen X.(2021) <arXiv:2105.03993>.

r-phia 0.3-2
Propagated dependencies: r-matrix@1.7-4 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/heliosdrm/phia
Licenses: GPL 3+
Build system: r
Synopsis: Post-Hoc Interaction Analysis
Description:

Analysis of terms in linear, generalized and mixed linear models, on the basis of multiple comparisons of factor contrasts. Specially suited for the analysis of interaction terms.

r-presspurt 1.0.2
Propagated dependencies: r-reticulate@1.44.1 r-gridextra@2.3 r-ggplot2@4.0.1 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/dkoslicki/PressPurt
Licenses: Expat
Build system: r
Synopsis: Indeterminacy of Networks via Press Perturbations
Description:

This is a computational package designed to identify the most sensitive interactions within a network which must be estimated most accurately in order to produce qualitatively robust predictions to a press perturbation. This is accomplished by enumerating the number of sign switches (and their magnitude) in the net effects matrix when an edge experiences uncertainty. The package produces data and visualizations when uncertainty is associated to one or more edges in the network and according to a variety of distributions. The software requires the network to be described by a system of differential equations but only requires as input a numerical Jacobian matrix evaluated at an equilibrium point. This package is based on Koslicki, D., & Novak, M. (2017) <doi:10.1007/s00285-017-1163-0>.

r-pkglite 0.2.5
Propagated dependencies: r-remotes@2.5.0 r-magrittr@2.0.4 r-crayon@1.5.3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://merck.github.io/pkglite/
Licenses: GPL 3
Build system: r
Synopsis: Compact Package Representations
Description:

This package provides a tool, grammar, and standard to represent and exchange R package source code as text files. Converts one or more source packages to a text file and restores the package structures from the file.

r-pytrendslongitudinalr 0.1.4
Dependencies: python@3.11.14 python-pandas@2.2.3
Propagated dependencies: r-reticulate@1.44.1 r-lubridate@1.9.4 r-jsonlite@2.0.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PytrendsLongitudinalR
Licenses: Expat
Build system: r
Synopsis: Create Longitudinal Google Trends Data
Description:

Google Trends provides cross-sectional and time-series data on searches, but lacks readily available longitudinal data. Researchers, who want to create longitudinal Google Trends on their own, face practical challenges, such as normalized counts that make it difficult to combine cross-sectional and time-series data and limitations in data formats and timelines that limit data granularity over extended time periods. This package addresses these issues and enables researchers to generate longitudinal Google Trends data. This package is built on pytrends', a Python library that acts as the unofficial Google Trends API to collect Google Trends data. As long as the Google Trends API', pytrends and all their dependencies are working, this package will work. During testing, we noticed that for the same input (keyword, topic, data_format, timeline), the output index can vary from time to time. Besides, if the keyword is not very popular, then the resulting dataset will contain a lot of zeros, which will greatly affect the final result. While this package has no control over the accuracy or quality of Google Trends data, once the data is created, this package coverts it to longitudinal data. In addition, the user may encounter a 429 Too Many Requests error when using cross_section() and time_series() to collect Google Trends data. This error indicates that the user has exceeded the rate limits set by the Google Trends API'. For more information about the Google Trends API - pytrends', visit <https://pypi.org/project/pytrends/>.

r-poth 0.3-0
Propagated dependencies: r-stringr@1.6.0 r-netmeta@3.3-1 r-mass@7.3-65 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/augustinewigle/poth
Licenses: GPL 2+
Build system: r
Synopsis: Precision of Treatment Hierarchy (POTH)
Description:

Calculate POTH for treatment hierarchies from frequentist and Bayesian network meta-analysis. POTH quantifies the certainty in a treatment hierarchy. Subset POTH, POTH residuals, and best k treatments POTH can also be calculated to improve interpretation of treatment hierarchies.

r-plgp 1.1-13
Propagated dependencies: r-tgp@2.4-23 r-mvtnorm@1.3-3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://bobby.gramacy.com/r_packages/plgp/
Licenses: LGPL 2.0+
Build system: r
Synopsis: Particle Learning of Gaussian Processes
Description:

Sequential Monte Carlo (SMC) inference for fully Bayesian Gaussian process (GP) regression and classification models by particle learning (PL) following Gramacy & Polson (2011) <doi:10.48550/arXiv.0909.5262>. The sequential nature of inference and the active learning (AL) hooks provided facilitate thrifty sequential design (by entropy) and optimization (by improvement) for classification and regression models, respectively. This package essentially provides a generic PL interface, and functions (arguments to the interface) which implement the GP models and AL heuristics. Functions for a special, linked, regression/classification GP model and an integrated expected conditional improvement (IECI) statistic provide for optimization in the presence of unknown constraints. Separable and isotropic Gaussian, and single-index correlation functions are supported. See the examples section of ?plgp and demo(package="plgp") for an index of demos.

r-profileci 1.1.1
Propagated dependencies: r-itp@1.2.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://paulnorthrop.github.io/profileCI/
Licenses: GPL 3+
Build system: r
Synopsis: Profiling a Log-Likelihood to Calculate Confidence Intervals
Description:

This package provides tools for profiling a user-supplied log-likelihood function to calculate confidence intervals for model parameters. Speed of computation can be improved by adjusting the step sizes in the profiling and/or starting the profiling from limits based on the approximate large sample normal distribution for the maximum likelihood estimator of a parameter. The accuracy of the limits can be set by the user. A plot method visualises the log-likelihood and confidence interval. Cases where the profile log-likelihood flattens above the value at which a confidence limit is defined can be handled, leading to a limit at plus or minus infinity. Disjoint confidence intervals will not be found.

r-paleobuddy 1.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/brpetrucci/paleobuddy
Licenses: GPL 3
Build system: r
Synopsis: Simulating Diversification Dynamics
Description:

Simulation of species diversification, fossil records, and phylogenies. While the literature on species birth-death simulators is extensive, including important software like paleotree and APE', we concluded there were interesting gaps to be filled regarding possible diversification scenarios. Here we strove for flexibility over focus, implementing a large array of regimens for users to experiment with and combine. In this way, paleobuddy can be used in complement to other simulators as a flexible jack of all trades, or, in the case of scenarios implemented only here, can allow for robust and easy simulations for novel situations. Environmental data modified from that in RPANDA': Morlon H. et al (2016) <doi:10.1111/2041-210X.12526>.

r-polca 1.6.0.2
Propagated dependencies: r-scatterplot3d@0.3-44 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/dlinzer/poLCA
Licenses: GPL 2+
Build system: r
Synopsis: Polytomous Variable Latent Class Analysis
Description:

Latent class analysis and latent class regression models for polytomous outcome variables. Also known as latent structure analysis.

r-przewodnik 0.16.12
Propagated dependencies: r-pogromcydanych@1.7.1 r-pbimisc@1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=Przewodnik
Licenses: GPL 2
Build system: r
Synopsis: Datasets and Functions Used in the Book 'Przewodnik po Pakiecie R'
Description:

Data sets and functions used in the polish book "Przewodnik po pakiecie R" (The Hitchhiker's Guide to the R). See more at <http://biecek.pl/R>. Among others you will find here data about housing prices, cancer patients, running times and many others.

r-phylopairs 0.1.1
Propagated dependencies: r-stanheaders@2.32.10 r-rstantools@2.5.0 r-rstan@2.32.7 r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-phytools@2.5-2 r-loo@2.8.0 r-bh@1.87.0-1 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=phylopairs
Licenses: GPL 3+
Build system: r
Synopsis: Comparative Analyses of Lineage-Pair Traits
Description:

Facilitates the testing of causal relationships among lineage-pair traits in a phylogenetically informed context. Lineage-pair traits are characters that are defined for pairs of lineages instead of individual taxa. Examples include the strength of reproductive isolation, range overlap, competition coefficient, diet niche similarity, and relative hybrid fitness. Users supply a lineage-pair dataset and a phylogeny. phylopairs calculates a covariance matrix for the pairwise-defined data and provides built-in models to test for relationships among variables while taking this covariance into account. Bayesian sampling is run through built-in Stan programs via the rstan package. The various models and methods that this package makes available are described in Anderson et al. (In Review), Coyne and Orr (1989) <doi:10.1111/j.1558-5646.1989.tb04233.x>, Fitzpatrick (2002) <doi:10.1111/j.0014-3820.2002.tb00860.x>, and Castillo (2007) <doi:10.1002/ece3.3093>.

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