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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-partialnetwork 1.1.2
Propagated dependencies: r-rcppprogress@0.4.2 r-rcppnumerical@0.6-0 r-rcppeigen@0.3.4.0.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-matrix@1.7-4 r-formula-tools@1.7.1 r-formula@1.2-5 r-foreach@1.5.2 r-dorng@1.8.6.2 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://github.com/ahoundetoungan/PartialNetwork
Licenses: GPL 3
Build system: r
Synopsis: Estimating Peer Effects Using Partial Network Data
Description:

This package implements IV-estimator and Bayesian estimator for linear-in-means Spatial Autoregressive (SAR) model (see LeSage, 1997 <doi:10.1177/016001769702000107>; Lee, 2004 <doi:10.1111/j.1468-0262.2004.00558.x>; Bramoullé et al., 2009 <doi:10.1016/j.jeconom.2008.12.021>), while assuming that only a partial information about the network structure is available. Examples are when the adjacency matrix is not fully observed or when only consistent estimation of the network formation model is available (see Boucher and Houndetoungan, 2025 <doi:10.48550/arXiv.2509.08145>).

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-phagecocktail 1.0.3
Propagated dependencies: r-stringr@1.6.0 r-smerc@1.8.4 r-rjsonio@2.0.0 r-readxl@1.4.5 r-factoextra@1.0.7 r-bipartite@2.23
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PhageCocktail
Licenses: GPL 3
Build system: r
Synopsis: Design of the Best Phage Cocktail
Description:

There are 4 possible methods: "ExhaustiveSearch"; "ExhaustivePhi"; "ClusteringSearch"; and "ClusteringPhi". "ExhaustiveSearch"--> gives you the best phage cocktail from a phage-bacteria infection network. It checks different phage cocktail sizes from 1 to 7 and only stops before if it lyses all bacteria. Other option is when users have decided not to obtain a phage cocktail size higher than a limit value. "ExhaustivePhi"--> firstly, it finds Phi out. Phi is a formula indicating the necessary phage cocktail size. Phi needs nestedness temperature and fill, which are internally calculated. This function will only look for the best combination (phage cocktail) with a Phi size. "ClusteringSearch"--> firstly, an agglomerative hierarchical clustering using Ward's algorithm is calculated for phages. They will be clustered according to bacteria lysed by them. PhageCocktail() chooses how many clusters are needed in order to select 1 phage per cluster. Using the phages selected during the clustering, it checks different phage cocktail sizes from 1 to 7 and only stops before if it lyses all bacteria. Other option is when users have decided not to obtain a phage cocktail size higher than a limit value. "ClusteringPhi"--> firstly, an agglomerative hierarchical clustering using Ward's algorithm is calculated for phages. They will be clustered according to bacteria lysed by them. PhageCocktail() chooses how many clusters are needed in order to select 1 phage per cluster. Once the function has one phage per cluster, it calculates Phi. If the number of clusters is less than Phi number, it will be changed to obtain, as minimum, this quantity of candidates (phages). Then, it calculates the best combination of Phi phages using those selected during the clustering with Ward algorithm. If you use PhageCocktail, please cite it as: "PhageCocktail: An R Package to Design Phage Cocktails from Experimental Phage-Bacteria Infection Networks". Marà a Victoria Dà az-Galián, Miguel A. Vega-Rodrà guez, Felipe Molina. Computer Methods and Programs in Biomedicine, 221, 106865, Elsevier Ireland, Clare, Ireland, 2022, pp. 1-9, ISSN: 0169-2607. <doi:10.1016/j.cmpb.2022.106865>.

r-pmr 1.2.5.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pmr
Licenses: GPL 2
Build system: r
Synopsis: Probability Models for Ranking Data
Description:

Descriptive statistics (mean rank, pairwise frequencies, and marginal matrix), Analytic Hierarchy Process models (with Saaty's and Koczkodaj's inconsistencies), probability models (Luce models, distance-based models, and rank-ordered logit models) and visualization with multidimensional preference analysis for ranking data are provided. Current, only complete rankings are supported by this 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-pivotea 1.0.2
Propagated dependencies: r-tidyr@1.3.1 r-rlang@1.1.6 r-purrr@1.2.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/matutosi/pivotea
Licenses: Expat
Build system: r
Synopsis: Create Pivot Table Easily
Description:

Pivot easily by specifying rows, columns, values and split.

r-pfim 7.0.2
Propagated dependencies: r-tibble@3.3.0 r-stringr@1.6.0 r-scales@1.4.0 r-s7@0.2.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-purrr@1.2.0 r-pracma@2.4.6 r-matrix@1.7-4 r-knitr@1.50 r-kableextra@1.4.0 r-inline@0.3.21 r-ggplot2@4.0.1 r-desolve@1.40 r-deriv@4.2.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: http://www.pfim.biostat.fr/
Licenses: GPL 3+
Build system: r
Synopsis: Population Fisher Information Matrix
Description:

Evaluate or optimize designs for nonlinear mixed effects models using the Fisher Information matrix. Methods used in the package refer to Mentré F, Mallet A, Baccar D (1997) <doi:10.1093/biomet/84.2.429>, Retout S, Comets E, Samson A, Mentré F (2007) <doi:10.1002/sim.2910>, Bazzoli C, Retout S, Mentré F (2009) <doi:10.1002/sim.3573>, Le Nagard H, Chao L, Tenaillon O (2011) <doi:10.1186/1471-2148-11-326>, Combes FP, Retout S, Frey N, Mentré F (2013) <doi:10.1007/s11095-013-1079-3> and Seurat J, Tang Y, Mentré F, Nguyen TT (2021) <doi:10.1016/j.cmpb.2021.106126>.

r-pgraph 1.6
Propagated dependencies: r-sam@1.2 r-glmnet@4.1-10 r-glasso@1.11 r-energy@1.7-12
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pgraph
Licenses: GPL 2
Build system: r
Synopsis: Build Dependency Graphs using Projection
Description:

This package implements a general framework for creating dependency graphs using projection as introduced in Fan, Feng and Xia (2019)<arXiv:1501.01617>. Both lasso and sparse additive model projections are implemented. Both Pearson correlation and distance covariance options are available to generate the graph.

r-petests 0.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PEtests
Licenses: GPL 3+
Build system: r
Synopsis: Power-Enhanced (PE) Tests for High-Dimensional Data
Description:

Two-sample power-enhanced mean tests, covariance tests, and simultaneous tests on mean vectors and covariance matrices for high-dimensional data. Methods of these PE tests are presented in Yu, Li, and Xue (2022) <doi:10.1080/01621459.2022.2126781>; Yu, Li, Xue, and Li (2022) <doi:10.1080/01621459.2022.2061354>.

r-pegs 0.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pegs
Licenses: GPL 3
Build system: r
Synopsis: Pseudo-Expectation Gauss-Seidel
Description:

This package provides a lightweight, dependency-free, and simplified implementation of the Pseudo-Expectation Gauss-Seidel (PEGS) algorithm. It fits the multivariate ridge regression model for genomic prediction Xavier and Habier (2022) <doi:10.1186/s12711-022-00730-w> and Xavier et al. (2025) <doi:10.1093/genetics/iyae179>, providing heritability estimates, genetic correlations, breeding values, and regression coefficient estimates for prediction. This package provides an alternative to the bWGR package by Xavier et al. (2019) <doi:10.1093/bioinformatics/btz794> by using LAPACK for its algebraic operations.

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-packagerank 0.9.7
Propagated dependencies: r-sugrrants@0.2.9 r-rversions@3.0.0 r-rcurl@1.98-1.17 r-r-utils@2.13.0 r-pkgsearch@3.1.5 r-patchwork@1.3.2 r-memoise@2.0.1 r-isocodes@2025.05.18 r-ggplot2@4.0.1 r-fasttime@1.1-0 r-data-table@1.17.8 r-curl@7.0.0 r-cranlogs@2.1.1 r-cachem@1.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/lindbrook/packageRank
Licenses: GPL 2+
Build system: r
Synopsis: Computation and Visualization of Package Download Counts and Percentile Ranks
Description:

Compute and visualize package download counts and percentile ranks from Posit/RStudio's CRAN mirror.

r-prompt 1.0.2
Propagated dependencies: r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/gaborcsardi/prompt
Licenses: Expat
Build system: r
Synopsis: Dynamic 'R' Prompt
Description:

Set the R prompt dynamically, from a function. The package contains some examples to include various useful dynamic information in the prompt: the status of the last command (success or failure); the amount of memory allocated by the current R process; the name of the R package(s) loaded by pkgload and/or devtools'; various git information: the name of the active branch, whether it is dirty, if it needs pushes pulls. You can also create your own prompt if you don't like the predefined examples.

r-plantecophys 1.4-6
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://bitbucket.org/remkoduursma/plantecophys
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Modelling and Analysis of Leaf Gas Exchange Data
Description:

Coupled leaf gas exchange model, A-Ci curve simulation and fitting, Ball-Berry stomatal conductance models, leaf energy balance using Penman-Monteith, Cowan-Farquhar optimization, humidity unit conversions. See Duursma (2015) <doi:10.1371/journal.pone.0143346>.

r-pendensity 0.2.13
Propagated dependencies: r-lattice@0.22-7 r-fda@6.3.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pendensity
Licenses: GPL 2+
Build system: r
Synopsis: Density Estimation with a Penalized Mixture Approach
Description:

Estimation of univariate (conditional) densities using penalized B-splines with automatic selection of optimal smoothing parameter.

r-pacta-multi-loanbook 0.1.1
Propagated dependencies: r-yesno@0.1.3 r-yaml@2.3.10 r-tidyr@1.3.1 r-scales@1.4.0 r-rlang@1.1.6 r-readxl@1.4.5 r-readr@2.1.6 r-r2dii-plot@0.5.2 r-r2dii-match@0.4.1 r-r2dii-data@0.6.1 r-r2dii-analysis@0.5.3 r-glue@1.8.0 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-ggalluvial@0.12.5 r-dplyr@1.1.4 r-config@0.3.2 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://rmi-pacta.github.io/pacta.multi.loanbook/
Licenses: Expat
Build system: r
Synopsis: Run 'PACTA' on Multiple Loan Books Easily
Description:

Run Paris Agreement Capital Transition Assessment ('PACTA') analyses on multiple loan books in a structured way. Provides access to standard PACTA metrics and additional PACTA'-related metrics for multiple loan books. Results take the form of csv files and plots and are exported to user-specified project paths.

r-prnsamplr 1.1.0
Propagated dependencies: r-rlang@1.1.6
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=prnsamplr
Licenses: Expat
Build system: r
Synopsis: Permanent Random Number Sampling
Description:

Survey sampling using permanent random numbers (PRN's). A solution to the problem of unknown overlap between survey samples, which leads to a low precision in estimates when the survey is repeated or combined with other surveys. The PRN solution is to supply the U(0, 1) random numbers to the sampling procedure, instead of having the sampling procedure generate them. In Lindblom (2014) <doi:10.2478/jos-2014-0047>, and therein cited papers, it is shown how this is carried out and how it improves the estimates. This package supports two common fixed-size sampling procedures (simple random sampling and probability-proportional-to-size sampling) and includes a function for transforming the PRN's in order to control the sample overlap.

r-poobly 0.1.2
Propagated dependencies: r-plm@2.6-7
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/cadam00/poobly
Licenses: GPL 3
Build system: r
Synopsis: Poolability Tests in Panel Data
Description:

Homogeneity tests of the coefficients in panel data. Currently, only the Hsiao test for determining coefficient homogeneity between the panel data individuals is implemented, as described in Hsiao (2022), "Analysis of Panel Data" (<doi:10.1017/9781009057745>).

r-pheindicatormethods 2.1.1
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-purrr@1.2.0 r-lifecycle@1.0.4 r-dplyr@1.1.4 r-broom@1.0.10
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PHEindicatormethods
Licenses: GPL 3
Build system: r
Synopsis: Common Public Health Statistics and their Confidence Intervals
Description:

This package provides functions to calculate commonly used public health statistics and their confidence intervals using methods approved for use in the production of Public Health England indicators such as those presented via Fingertips (<https://fingertips.phe.org.uk/>). It provides functions for the generation of proportions, crude rates, means, directly standardised rates, indirectly standardised rates, standardised mortality ratios, slope and relative index of inequality and life expectancy. Statistical methods are referenced in the following publications. Breslow NE, Day NE (1987) <doi:10.1002/sim.4780080614>. Dobson et al (1991) <doi:10.1002/sim.4780100317>. Armitage P, Berry G (2002) <doi:10.1002/9780470773666>. Wilson EB. (1927) <doi:10.1080/01621459.1927.10502953>. Altman DG et al (2000, ISBN: 978-0-727-91375-3). Chiang CL. (1968, ISBN: 978-0-882-75200-6). Newell C. (1994, ISBN: 978-0-898-62451-9). Eayres DP, Williams ES (2004) <doi:10.1136/jech.2003.009654>. Silcocks PBS et al (2001) <doi:10.1136/jech.55.1.38>. Low and Low (2004) <doi:10.1093/pubmed/fdh175>. Fingertips Public Health Technical Guide: <https://fingertips.phe.org.uk/profile/guidance/supporting-information/PH-methods/>.

r-ptmixed 1.1.3
Propagated dependencies: r-numderiv@2016.8-1.1 r-mvtnorm@1.3-3 r-moments@0.14.1 r-matrixcalc@1.0-6 r-lme4@1.1-37 r-glmmadaptive@0.9-7
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://mirkosignorelli.github.io/r
Licenses: GPL 3
Build system: r
Synopsis: Poisson-Tweedie Generalized Linear Mixed Model
Description:

Fits the Poisson-Tweedie generalized linear mixed model described in Signorelli et al. (2021, <doi:10.1177/1471082X20936017>). Likelihood approximation based on adaptive Gauss Hermite quadrature rule.

r-plotftir 1.2.1
Propagated dependencies: r-scales@1.4.0 r-rlang@1.1.6 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/NRCan/PlotFTIR
Licenses: GPL 3+
Build system: r
Synopsis: Plot FTIR Spectra
Description:

The goal of PlotFTIR is to easily and quickly kick-start the production of journal-quality Fourier Transform Infra-Red (FTIR) spectral plots in R using ggplot2'. The produced plots can be published directly or further modified by ggplot2 functions. L'objectif de PlotFTIR est de démarrer facilement et rapidement la production des tracés spectraux de spectroscopie infrarouge à transformée de Fourier (IRTF) de qualité journal dans R à l'aide de ggplot2'. Les tracés produits peuvent être publiés directement ou modifiés davantage par les fonctions ggplot2'.

r-pdi 0.4.2
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-readxl@1.4.5 r-randomforest@4.7-1.2 r-purrr@1.2.0 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://jasenfinch.github.io/pdi
Licenses: GPL 3
Build system: r
Synopsis: Phenotypic Index Measures for Oak Decline Severity
Description:

Oak declines are complex disease syndromes and consist of many visual indicators that include aspects of tree size, crown condition and trunk condition. This can cause difficulty in the manual classification of symptomatic and non-symptomatic trees from what is in reality a broad spectrum of oak tree health condition. Two phenotypic oak decline indexes have been developed to quantitatively describe and differentiate oak decline syndromes in Quercus robur. This package provides a toolkit to generate these decline indexes from phenotypic descriptors using the machine learning algorithm random forest. The methodology for generating these indexes is outlined in Finch et al. (2121) <doi:10.1016/j.foreco.2021.118948>.

r-panelhetero 1.0.1
Propagated dependencies: r-rearrangement@2.1 r-kernsmooth@2.23-26 r-ggplot2@4.0.1 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://tkhdyanagi.github.io/panelhetero/
Licenses: Expat
Build system: r
Synopsis: Panel Data Analysis with Heterogeneous Dynamics
Description:

Understanding the dynamics of potentially heterogeneous variables is important in statistical applications. This package provides tools for estimating the degree of heterogeneity across cross-sectional units in the panel data analysis. The methods are developed by Okui and Yanagi (2019) <doi:10.1016/j.jeconom.2019.04.036> and Okui and Yanagi (2020) <doi:10.1093/ectj/utz019>.

r-psp 1.0.5
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/lenarddome/psp
Licenses: GPL 3+
Build system: r
Synopsis: Parameter Space Partitioning MCMC for Global Model Evaluation
Description:

This package implements an n-dimensional parameter space partitioning algorithm for evaluating the global behaviour of formal computational models as described by Pitt, Kim, Navarro and Myung (2006) <doi:10.1037/0033-295X.113.1.57>.

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