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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-peacots 1.3.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=peacots
Licenses: GPL 3
Build system: r
Synopsis: Periodogram Peaks in Correlated Time Series
Description:

Calculates the periodogram of a time series, maximum-likelihood fits an Ornstein-Uhlenbeck state space (OUSS) null model and evaluates the statistical significance of periodogram peaks against the OUSS null hypothesis. The OUSS is a parsimonious model for stochastically fluctuating variables with linear stabilizing forces, subject to uncorrelated measurement errors. Contrary to the classical white noise null model for detecting cyclicity, the OUSS model can account for temporal correlations typically occurring in ecological and geological time series. Citation: Louca, Stilianos and Doebeli, Michael (2015) <doi:10.1890/14-0126.1>.

r-probout 1.1.2
Propagated dependencies: r-mclust@6.1.2 r-mass@7.3-65 r-fnn@1.1.4.1
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: Unsupervised Multivariate Outlier Probabilities for Large Datasets
Description:

Estimates unsupervised outlier probabilities for multivariate numeric data with many observations from a nonparametric outlier statistic.

r-pakpmics2018mn 0.1.0
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/myaseen208/PakPMICS2018mn
Licenses: GPL 2
Build system: r
Synopsis: Multiple Indicator Cluster Survey (MICS) 2017-18 Men Questionnaire Data for Punjab, Pakistan
Description:

This package provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 Men questionnaire data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of Sustainable Development Goals (SDGs) monitoring, as the survey produces information on 32 global Sustainable Development Goals (SDGs) indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using probability proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household (<http://www.mics.unicef.org/surveys>).

r-pointfore 0.2.0
Propagated dependencies: r-sandwich@3.1-1 r-mass@7.3-65 r-lubridate@1.9.4 r-gmm@1.9-1 r-ggplot2@4.0.1 r-car@3.1-3 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PointFore
Licenses: CC0
Build system: r
Synopsis: Interpretation of Point Forecasts as State-Dependent Quantiles and Expectiles
Description:

Estimate specification models for the state-dependent level of an optimal quantile/expectile forecast. Wald Tests and the test of overidentifying restrictions are implemented. Plotting of the estimated specification model is possible. The package contains two data sets with forecasts and realizations: the daily accumulated precipitation at London, UK from the high-resolution model of the European Centre for Medium-Range Weather Forecasts (ECMWF, <https://www.ecmwf.int/>) and GDP growth Greenbook data by the US Federal Reserve. See Schmidt, Katzfuss and Gneiting (2015) <arXiv:1506.01917> for more details on the identification and estimation of a directive behind a point forecast.

r-pharmaversesdtm 1.4.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://pharmaverse.github.io/pharmaversesdtm/
Licenses: ASL 2.0
Build system: r
Synopsis: SDTM Test Data for the 'Pharmaverse' Family of Packages
Description:

This package provides a set of Study Data Tabulation Model (SDTM) datasets from the Clinical Data Interchange Standards Consortium (CDISC) pilot project used for testing and developing Analysis Data Model (ADaM) datasets inside the pharmaverse family of packages. SDTM dataset specifications are described in the CDISC SDTM implementation guide, accessible by creating a free account on <https://www.cdisc.org/>.

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-psm3mkv 0.3.2
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-survival@3.8-3 r-stringr@1.6.0 r-simplicialcubature@1.3 r-rlang@1.1.6 r-purrr@1.2.0 r-pharmaverseadam@1.2.0 r-ggplot2@4.0.1 r-flexsurv@2.3.2 r-dplyr@1.1.4 r-admiral@1.4.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://merck.github.io/psm3mkv/
Licenses: GPL 3+
Build system: r
Synopsis: Evaluate Partitioned Survival and State Transition Models
Description:

Fits and evaluates three-state partitioned survival analyses (PartSAs) and Markov models (clock forward or clock reset) to progression and overall survival data typically collected in oncology clinical trials. These model structures are typically considered in cost-effectiveness modeling in advanced/metastatic cancer indications. Muston (2024). "Informing structural assumptions for three state oncology cost-effectiveness models through model efficiency and fit". Applied Health Economics and Health Policy.

r-pensynth 0.8.1
Propagated dependencies: r-matrix@1.7-4 r-lifecycle@1.0.4 r-cli@3.6.5 r-clarabel@0.11.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/vankesteren/pensynth
Licenses: Expat
Build system: r
Synopsis: Penalized Synthetic Control Estimation
Description:

Estimate penalized synthetic control models and perform hold-out validation to determine their penalty parameter. This method is based on the work by Abadie & L'Hour (2021) <doi:10.1080/01621459.2021.1971535>. Penalized synthetic controls smoothly interpolate between one-to-one matching and the synthetic control method.

r-promethee123 0.1.0
Propagated dependencies: r-ggplot2@4.0.1 r-cowplot@1.2.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=promethee123
Licenses: GPL 3
Build system: r
Synopsis: PROMETHEE I, II, and III Methods
Description:

The PROMETHEE method is a multi-criteria decision-making method addressing with outranking problems. The method establishes a preference structure between the alternatives, having a preference function for each criterion. IN this context, three variants of the method is carried out: PROMETHEE I (Partial Outranking), PROMETHEE II (Total Outranking), and PROMETHEE III (Outranking by Intervals).

r-provexplainr 1.1.1
Propagated dependencies: r-stringr@1.6.0 r-provparser@1.0 r-dplyr@1.1.4 r-digest@0.6.39 r-diffobj@0.3.6
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 FSDG-compatible
Build system: r
Synopsis: Compare Provenance Collections to Explain Changed Script Outputs
Description:

Inspects provenance collected by the rdt or rdtLite packages, or other tools providing compatible PROV JSON output created by the execution of a script, and find differences between two provenance collections. Factors under examination included the hardware and software used to execute the script, versions of attached libraries, use of global variables, modified inputs and outputs, and changes in main and sourced scripts. Based on detected changes, provExplainR can be used to study how these factors affect the behavior of the script and generate a promising diagnosis of the causes of different script results. More information about rdtLite and associated tools is available at <https://github.com/End-to-end-provenance/> and Barbara Lerner, Emery Boose, and Luis Perez (2018), Using Introspection to Collect Provenance in R, Informatics, <doi:10.3390/informatics5010012>.

r-polyqtlr 0.1.1
Propagated dependencies: r-reshape2@1.4.5 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-rcolorbrewer@1.1-3 r-nlme@3.1-168 r-knitr@1.50 r-hmisc@5.2-4 r-foreach@1.5.2 r-doparallel@1.0.17 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=polyqtlR
Licenses: GPL 3
Build system: r
Synopsis: QTL Analysis in Autopolyploid Bi-Parental F1 Populations
Description:

Quantitative trait loci (QTL) analysis and exploration of meiotic patterns in autopolyploid bi-parental F1 populations. For all ploidy levels, identity-by-descent (IBD) probabilities can be estimated. Significance thresholds, exploring QTL allele effects and visualising results are provided. For more background and to reference the package see <doi:10.1093/bioinformatics/btab574>.

r-pgkdesphere 1.0.2
Propagated dependencies: r-rotasym@1.2.0 r-rgl@1.3.31 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-movmf@0.2-9 r-matrixstats@1.5.0 r-dirstats@0.1.10 r-directional@7.3 r-circular@0.5-2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pgKDEsphere
Licenses: GPL 2+
Build system: r
Synopsis: Parametrically Guided Kernel Density Estimator for Spherical Data
Description:

Nonparametric density estimation for (hyper)spherical data by means of a parametrically guided kernel estimator (Alonso-Pena et al. (2024) <doi:10.1111/sjos.12737>. The package also allows the data-driven selection of the smoothing parameter and the representation of the estimated density for circular and spherical data. Estimators of the density without guide can also be obtained.

r-posratiodist 1.2.1
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=PosRatioDist
Licenses: GPL 2+
Build system: r
Synopsis: Quotient of Random Variables Conditioned to the Positive Quadrant
Description:

Computes the exact probability density function of X/Y conditioned on positive quadrant for series of bivariate distributions,for more details see Nadarajah,Song and Si (2019) <DOI:10.1080/03610926.2019.1576893>.

r-pakpc2017 1.0.0
Propagated dependencies: r-magrittr@2.0.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/MYaseen208/PakPC2017
Licenses: GPL 2
Build system: r
Synopsis: Pakistan Population Census 2017
Description:

This package provides data sets and functions for exploration of Pakistan Population Census 2017 (<http://www.pbscensus.gov.pk/>).

r-primefactr 0.1.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/privefl/primefactr
Licenses: GPL 3
Build system: r
Synopsis: Use Prime Factorization for Computations
Description:

Use Prime Factorization for simplifying computations, for instance for ratios of large factorials.

r-pkgndep 1.99.3
Propagated dependencies: r-hash@2.2.6.3 r-globaloptions@0.1.2 r-getoptlong@1.0.5 r-complexheatmap@2.26.0 r-brew@1.0-10 r-biocversion@3.22.0 r-biocmanager@1.30.27
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/jokergoo/pkgndep
Licenses: Expat
Build system: r
Synopsis: Analyze Dependency Heaviness of R Packages
Description:

This package provides a new metric named dependency heaviness is proposed that measures the number of additional dependency packages that a parent package brings to its child package and are unique to the dependency packages imported by all other parents. The dependency heaviness analysis is visualized by a customized heatmap. The package is described in <doi:10.1093/bioinformatics/btac449>. We have also performed the dependency heaviness analysis on the CRAN/Bioconductor package ecosystem and the results are implemented as a web-based database which provides comprehensive tools for querying dependencies of individual R packages. The systematic analysis on the CRAN/Bioconductor ecosystem is described in <doi:10.1016/j.jss.2023.111610>. From pkgndep version 2.0.0, the heaviness database includes snapshots of the CRAN/Bioconductor ecosystems for many old R versions.

r-parallelplot 0.4.0
Propagated dependencies: r-htmlwidgets@1.6.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://gitlab.com/drti/parallelplot
Licenses: Expat
Build system: r
Synopsis: `htmlwidget` for a Parallel Coordinates Plot
Description:

Create a parallel coordinates plot, using `htmlwidgets` package and `d3.js`.

r-ptsr 0.1.3
Propagated dependencies: r-suppdists@1.1-9.9 r-numderiv@2016.8-1.1 r-extradistr@1.10.0 r-actuar@3.3-6
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PTSR
Licenses: GPL 3+
Build system: r
Synopsis: Positive Time Series Regression
Description:

This package provides a collection of functions to simulate, estimate and forecast a wide range of regression based dynamic models for positive time series. This package implements the results presented in Prass, T.S.; Pumi, G.; Taufemback, C.G. and Carlos, J.H. (2025). "Positive time series regression models: theoretical and computational aspects". Computational Statistics 40, 1185รข 1215. <doi:10.1007/s00180-024-01531-z>.

r-phonetisr 0.1.0
Propagated dependencies: r-unicode@16.0.0-1 r-tibble@3.3.0 r-stringr@1.6.0 r-stringi@1.8.7 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/stefanocoretta/phonetisr
Licenses: Expat
Build system: r
Synopsis: Naive IPA Tokeniser
Description:

It provides users with functions to parse International Phonetic Alphabet (IPA) transcriptions into individual phones (tokenisation) based on default IPA symbols and optional user specified multi-character phones. The tokenised transcriptions can be used for obtaining counts of phones or for searching for words matching phonetic patterns.

r-precipe 3.0.3
Dependencies: proj@9.3.1 gdal@3.8.2
Propagated dependencies: r-twc@0.0.2 r-scales@1.4.0 r-raster@3.6-32 r-openair@2.19.0 r-magrittr@2.0.4 r-ggpubr@0.6.2 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/MiRoVaGo/pRecipe
Licenses: GPL 3
Build system: r
Synopsis: Precipitation R Recipes
Description:

An open-access tool/framework to download, validate, visualize, and analyze multi-source precipitation data. More information and an example of implementation can be found in Vargas Godoy and Markonis (2023, <doi:10.1016/j.envsoft.2023.105711>).

r-poppsiseqr 1.0.2
Propagated dependencies: r-withr@3.0.2 r-tidyr@1.3.1 r-s4vectors@0.48.0 r-rtracklayer@1.70.0 r-rlang@1.1.6 r-patchwork@1.3.2 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-ggbio@1.58.0 r-genomicranges@1.62.0 r-dplyr@1.1.4 r-devtools@2.4.6
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/csoeder/PopPsiSeq
Licenses: Expat
Build system: r
Synopsis: Process and Visualize Evolve & Resequence Experiments
Description:

Handle data from evolve and resequence experiments. Measured allele frequencies (e.g., from variants called from high-throughput sequencing data) are compared using an update of the PsiSeq algorithm (Earley, Eric and Corbin Jones (2011) <doi:10.1534/genetics.111.129445>). Functions for saving and loading important files are also included, as well as functions for basic data visualization.

r-prcr 0.2.1
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-purrr@1.2.0 r-magrittr@2.0.4 r-lpsolve@5.6.23 r-irr@0.84.1 r-ggplot2@4.0.1 r-forcats@1.0.1 r-dplyr@1.1.4 r-class@7.3-23
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/jrosen48/prcr
Licenses: Expat
Build system: r
Synopsis: Person-Centered Analysis
Description:

This package provides an easy-to-use yet adaptable set of tools to conduct person-center analysis using a two-step clustering procedure. As described in Bergman and El-Khouri (1999) <DOI:10.1002/(SICI)1521-4036(199910)41:6%3C753::AID-BIMJ753%3E3.0.CO;2-K>, hierarchical clustering is performed to determine the initial partition for the subsequent k-means clustering procedure.

r-protoclust 1.6.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=protoclust
Licenses: GPL 2
Build system: r
Synopsis: Hierarchical Clustering with Prototypes
Description:

This package performs minimax linkage hierarchical clustering. Every cluster has an associated prototype element that represents that cluster as described in Bien, J., and Tibshirani, R. (2011), "Hierarchical Clustering with Prototypes via Minimax Linkage," The Journal of the American Statistical Association, 106(495), 1075-1084.

r-pooh 0.3-2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: http://www.stat.umn.edu/geyer/pooh/
Licenses: Expat
Build system: r
Synopsis: Partial Orders and Relations
Description:

Finds equivalence classes corresponding to a symmetric relation or undirected graph. Finds total order consistent with partial order or directed graph (so-called topological sort).

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Total results: 68658