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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-powerly 1.10.0
Propagated dependencies: r-splines2@0.5.4 r-rlang@1.1.6 r-r6@2.6.1 r-quadprog@1.5-8 r-qgraph@1.9.8 r-patchwork@1.3.2 r-parabar@1.4.2 r-mvtnorm@1.3-3 r-ggplot2@4.0.1 r-bootnet@1.6
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://powerly.dev
Licenses: Expat
Build system: r
Synopsis: Sample Size Analysis for Psychological Networks and More
Description:

An implementation of the sample size computation method for network models proposed by Constantin et al. (2023) <doi:10.1037/met0000555>. The implementation takes the form of a three-step recursive algorithm designed to find an optimal sample size given a model specification and a performance measure of interest. It starts with a Monte Carlo simulation step for computing the performance measure and a statistic at various sample sizes selected from an initial sample size range. It continues with a monotone curve-fitting step for interpolating the statistic across the entire sample size range. The final step employs stratified bootstrapping to quantify the uncertainty around the fitted curve.

r-pijavski 1.0.5
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=Pijavski
Licenses: LGPL 3
Build system: r
Synopsis: Global Univariate Minimization
Description:

Global univariate minimization of Lipschitz functions is performed by using Pijavski method, which was published in Pijavski (1972) <DOI:10.1016/0041-5553(72)90115-2>.

r-predicts 0.1-19
Propagated dependencies: r-terra@1.8-86
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://rspatial.org/sdm/
Licenses: GPL 3+
Build system: r
Synopsis: Spatial Prediction Tools
Description:

This package provides methods for spatial predictive modeling, especially for spatial distribution models. This includes algorithms for model fitting and prediction, as well as methods for model evaluation.

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-pampal 1.4.4
Propagated dependencies: r-xml2@1.5.0 r-tuner@1.4.7 r-tidyr@1.3.1 r-signal@1.8-1 r-shiny@1.11.1 r-seewave@2.2.4 r-rsqlite@2.4.4 r-rlang@1.1.6 r-reticulate@1.44.1 r-purrr@1.2.0 r-pammisc@1.12.7 r-pambinaries@1.9.3 r-lubridate@1.9.4 r-knitr@1.50 r-ggplot2@4.0.1 r-geosphere@1.5-20 r-gam@1.22-6 r-future-apply@1.20.0 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://cran.r-project.org/package=PAMpal
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Load and Process Passive Acoustic Data
Description:

This package provides tools for loading and processing passive acoustic data. Read in data that has been processed in Pamguard (<https://www.pamguard.org/>), apply a suite processing functions, and export data for reports or external modeling tools. Parameter calculations implement methods by Oswald et al (2007) <doi:10.1121/1.2743157>, Griffiths et al (2020) <doi:10.1121/10.0001229> and Baumann-Pickering et al (2010) <doi:10.1121/1.3479549>.

r-pcpr 1.0.0
Propagated dependencies: r-tidyselect@1.2.1 r-rlang@1.1.6 r-purrr@1.2.0 r-progressr@0.18.0 r-magrittr@2.0.4 r-future@1.68.0 r-furrr@0.3.1 r-foreach@1.5.2 r-dplyr@1.1.4 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://columbia-prime.github.io/pcpr/
Licenses: GPL 3+
Build system: r
Synopsis: Principal Component Pursuit for Environmental Epidemiology
Description:

Implementation of the pattern recognition technique Principal Component Pursuit tailored to environmental health data, as described in Gibson et al (2022) <doi:10.1289/EHP10479>.

r-preprocessrecordlinkage 1.0.1
Propagated dependencies: r-tm@0.7-16 r-syn@0.1.0 r-stringr@1.6.0 r-recordlinkage@0.4-12.6 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=PreProcessRecordLinkage
Licenses: GPL 3
Build system: r
Synopsis: Preprocessing Record Linkage
Description:

In this record linkage package, data preprocessing has been meticulously executed to cover a wide range of datasets, ensuring that variable names are standardized using synonyms. This approach facilitates seamless data integration and analysis across various datasets. While users have the flexibility to modify variable names, the system intelligently ensures that changes are only permitted when they do not compromise data consistency or essential variable essence.

r-printtree 0.2.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/PrigasG/printtree
Licenses: Expat
Build system: r
Synopsis: Print Directory Trees for R Projects and Folders
Description:

This package provides tools to print a compact, readable directory tree for a folder or project. The package can automatically detect common project roots (e.g., RStudio .Rproj files) and formats output for quick inspection of code and data organization. It supports typical tree customizations such as limiting depth, excluding files using ignore patterns, and producing clean, aligned text output suitable for console use, reports, and reproducible documentation. A snapshot helper can also render the tree output to a PNG image for sharing in issues, teaching material, or project documentation.

r-pharmaverseadam 1.2.0
Propagated dependencies: r-tibble@3.3.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://pharmaverse.github.io/pharmaverseadam/
Licenses: FSDG-compatible
Build system: r
Synopsis: ADaM Test Data for the 'Pharmaverse' Family of Packages
Description:

This package provides a set of Analysis Data Model (ADaM) datasets constructed using the Study Data Tabulation Model (SDTM) datasets contained in the pharmaversesdtm package and the template scripts from the admiral family of packages. ADaM dataset specifications are described in the CDISC ADaM implementation guide, accessible by creating a free account on <https://www.cdisc.org/>.

r-proliferativeindex 1.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=ProliferativeIndex
Licenses: Expat
Build system: r
Synopsis: Calculates and Analyzes the Proliferative Index
Description:

This package provides functions for calculating and analyzing the proliferative index (PI) from an RNA-seq dataset. As described in Ramaker & Lasseigne, et al. bioRxiv, 2016 <doi:10.1101/063057>.

r-peacesciencer 1.2.0
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-stevemisc@1.9.0 r-rlang@1.1.6 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-isard@0.1.0 r-geosphere@1.5-20 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/svmiller/peacesciencer/
Licenses: GPL 2
Build system: r
Synopsis: Tools and Data for Quantitative Peace Science Research
Description:

These are useful tools and data sets for the study of quantitative peace science. The goal for this package is to include tools and data sets for doing original research that mimics well what a user would have to previously get from a software package that may not be well-sourced or well-supported. Those software bundles were useful the extent to which they encourage replications of long-standing analyses by starting the data-generating process from scratch. However, a lot of the functionality can be done relatively quickly and more transparently in the R programming language.

r-panelselect 1.0.0
Propagated dependencies: r-statmod@1.5.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-pbv@0.5-47 r-pbivnorm@0.6.0 r-panelcount@2.0.1 r-maxlik@1.5-2.1 r-mass@7.3-65 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=PanelSelect
Licenses: GPL 3+
Build system: r
Synopsis: Panel Sample Selection Models
Description:

Extends the Heckman selection framework to panel data with individual random effects. The first stage models participation via a panel Probit specification, while the second stage can take a panel linear, Probit, Poisson, or Poisson log-normal form. Model details are provided in Bailey and Peng (2025) <doi:10.2139/ssrn.5475626> and Peng and Van den Bulte (2024) <doi:10.1287/mnsc.2019.01897>.

r-polycrossdesigns 1.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PolycrossDesigns
Licenses: GPL 2+
Build system: r
Synopsis: Polycross Designs ("PolycrossDesigns")
Description:

This package provides a polycross is the pollination by natural hybridization of a group of genotypes, generally selected, grown in isolation from other compatible genotypes in such a way to promote random open pollination. A particular practical application of the polycross method occurs in the production of a synthetic variety resulting from cross-pollinated plants. Laying out these experiments in appropriate designs, known as polycross designs, would not only save experimental resources but also gather more information from the experiment. Different experimental situations may arise in polycross nurseries which may be requiring different polycross designs (Varghese et. al. (2015) <doi:10.1080/02664763.2015.1043860>. " Experimental designs for open pollination in polycross trials"). This package contains a function named PD() which generates nine types of polycross designs suitable for various experimental situations.

r-pylintr 0.1.0
Propagated dependencies: r-rstudioapi@0.17.1 r-htmlwidgets@1.6.4 r-fansi@1.0.7
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/stla/pylintR
Licenses: GPL 3
Build system: r
Synopsis: Lint 'Python' Files with a R Command or a 'RStudio' Addin
Description:

Allow to run pylint on Python files with a R command or a RStudio addin. The report appears in the RStudio viewer pane as a formatted HTML file.

r-portes 6.0
Propagated dependencies: r-vars@1.6-1 r-forecast@8.24.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=portes
Licenses: GPL 2+
Build system: r
Synopsis: Portmanteau Tests for Time Series Models
Description:

This package contains common univariate and multivariate portmanteau test statistics for time series models. These tests are based on using asymptotic distributions such as chi-square distribution and based on using the Monte Carlo significance tests. Also, it can be used to simulate from univariate and multivariate seasonal time series models.

r-pprank 0.1.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=ppRank
Licenses: GPL 3
Build system: r
Synopsis: Classification of Algorithms
Description:

This package implements the Bi-objective Lexicographical Classification method and Performance Assessment Ratio at 10% metric for algorithm classification. Constructs matrices representing algorithm performance under multiple criteria, facilitating decision-making in algorithm selection and evaluation. Analyzes and compares algorithm performance based on various metrics to identify the most suitable algorithms for specific tasks. This package includes methods for algorithm classification and evaluation, with examples provided in the documentation. Carvalho (2019) presents a statistical evaluation of algorithmic computational experimentation with infeasible solutions <doi:10.48550/arXiv.1902.00101>. Moreira and Carvalho (2023) analyze power in preprocessing methodologies for datasets with missing values <doi:10.1080/03610918.2023.2234683>.

r-piqp 0.2.2
Propagated dependencies: r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-r6@2.6.1 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://predict-epfl.github.io/piqp-r/
Licenses: FreeBSD
Build system: r
Synopsis: R Interface to Proximal Interior Point Quadratic Programming Solver
Description:

An embedded proximal interior point quadratic programming solver, which can solve dense and sparse quadratic programs, described in Schwan, Jiang, Kuhn, and Jones (2023) <doi:10.48550/arXiv.2304.00290>. Combining an infeasible interior point method with the proximal method of multipliers, the algorithm can handle ill-conditioned convex quadratic programming problems without the need for linear independence of the constraints. The solver is written in header only C++ 14 leveraging the Eigen library for vectorized linear algebra. For small dense problems, vectorized instructions and cache locality can be exploited more efficiently. Allocation free problem updates and re-solves are also provided.

r-planr 0.6.3
Propagated dependencies: r-tidyr@1.3.1 r-rcpproll@0.3.1 r-magrittr@2.0.4 r-lubridate@1.9.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/nguyennico/planr
Licenses: Expat
Build system: r
Synopsis: Tools for Supply Chain Management, Demand and Supply Planning
Description:

Perform flexible and quick calculations for Demand and Supply Planning, such as projected inventories and coverages, as well as replenishment plan. For any time bucket, daily, weekly or monthly, and any granularity level, product or group of products.

r-pdp 0.8.3
Propagated dependencies: r-rlang@1.1.6 r-lattice@0.22-7 r-ggplot2@4.0.1 r-foreach@1.5.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/bgreenwell/pdp
Licenses: GPL 2+
Build system: r
Synopsis: Partial Dependence Plots
Description:

This package provides a general framework for constructing partial dependence (i.e., marginal effect) plots from various types machine learning models in R.

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-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-pvar 2.2.7
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=pvar
Licenses: GPL 2
Build system: r
Synopsis: Calculation and Application of p-Variation
Description:

The calculation of p-variation of the finite sample data. This package is a realisation of the procedure described in Butkus, V. & Norvaisa, R. Lith Math J (2018). <doi: 10.1007/s10986-018-9414-3> The formal definitions and reference into literature are given in vignette.

r-ppdiag 0.1.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://owenward.github.io/ppdiag/
Licenses: Expat
Build system: r
Synopsis: Diagnosis and Visualizations Tools for Temporal Point Processes
Description:

This package provides a suite of diagnostic tools for univariate point processes. This includes tools for simulating and fitting both common and more complex temporal point processes. We also include functions to visualise these point processes and collect existing diagnostic tools of Brown et al. (2002) <doi:10.1162/08997660252741149> and Wu et al. (2021) <doi:10.1002/9781119821588.ch7>, which can be used to assess the fit of a chosen point process model.

r-pupmsi 0.1.0
Propagated dependencies: r-nls2@0.3-4 r-minpack-lm@1.2-4 r-metrics@0.1.4 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=PUPMSI
Licenses: GPL 2
Build system: r
Synopsis: Moisture Sorption Isotherm Modeling Program
Description:

This package contains sixteen moisture sorption isotherm models, which evaluate the fitness of adsorption and desorption curves for further understanding of the relationship between moisture content and water activity. Fitness evaluation is conducted through parameter estimation and error analysis. Moreover, graphical representation, hysteresis area estimation, and isotherm classification through the equation of Blahovec & Yanniotis (2009) <doi:10.1016/j.jfoodeng.2008.08.007> which is based on the classification system introduced by Brunauer et. al. (1940) <doi:10.1021/ja01864a025> are also included for the visualization of models and hysteresis.

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