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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-pcdid 1.0.0
Propagated dependencies: r-sandwich@3.1-1 r-lmtest@0.9-40
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/adamwang15/pcdid
Licenses: GPL 3+
Build system: r
Synopsis: Principal Components Difference-in-Differences
Description:

This package implements the Principal Components Difference-in-Differences estimators as described in Chan, M. K., & Kwok, S. S. (2022) <doi:10.1080/07350015.2021.1914636>.

r-partition 0.2.2
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-purrr@1.2.0 r-progress@1.2.3 r-pillar@1.11.1 r-mass@7.3-65 r-magrittr@2.0.4 r-infotheo@1.2.0.1 r-ggplot2@4.0.1 r-forcats@1.0.1 r-dplyr@1.1.4 r-crayon@1.5.3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://uscbiostats.github.io/partition/
Licenses: Expat
Build system: r
Synopsis: Agglomerative Partitioning Framework for Dimension Reduction
Description:

This package provides a fast and flexible framework for agglomerative partitioning. partition uses an approach called Direct-Measure-Reduce to create new variables that maintain the user-specified minimum level of information. Each reduced variable is also interpretable: the original variables map to one and only one variable in the reduced data set. partition is flexible, as well: how variables are selected to reduce, how information loss is measured, and the way data is reduced can all be customized. partition is based on the Partition framework discussed in Millstein et al. (2020) <doi:10.1093/bioinformatics/btz661>.

r-plotluck 1.1.1
Propagated dependencies: r-scales@1.4.0 r-rcolorbrewer@1.1-3 r-quantreg@6.1 r-plyr@1.8.9 r-hmisc@5.2-4 r-hexbin@1.28.5 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/stefan-schroedl/plotluck
Licenses: Expat
Build system: r
Synopsis: 'ggplot2' Version of "I'm Feeling Lucky!"
Description:

Examines the characteristics of a data frame and a formula to automatically choose the most suitable type of plot out of the following supported options: scatter, violin, box, bar, density, hexagon bin, spine plot, and heat map. The aim of the package is to let the user focus on what to plot, rather than on the "how" during exploratory data analysis. It also automates handling of observation weights, logarithmic axis scaling, reordering of factor levels, and overlaying smoothing curves and median lines. Plots are drawn using ggplot2'.

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-proscorer 0.0.4
Propagated dependencies: r-proscorertools@0.0.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/raybaser/PROscorer
Licenses: Expat
Build system: r
Synopsis: Functions to Score Commonly-Used Patient-Reported Outcome (PRO) Measures and Other Psychometric Instruments
Description:

An extensible repository of accurate, up-to-date functions to score commonly used patient-reported outcome (PRO), quality of life (QOL), and other psychometric and psychological measures. PROscorer', together with the PROscorerTools package, is a system to facilitate the incorporation of PRO measures into research studies and clinical settings in a scientifically rigorous and reproducible manner. These packages and their vignettes are intended to help establish and promote best practices for scoring PRO and PRO-like measures in research. The PROscorer Instrument Descriptions vignette contains descriptions of each instrument scored by PROscorer', complete with references. These instrument descriptions are suitable for inclusion in formal study protocol documents, grant proposals, and manuscript Method sections. Each PROscorer function is composed of helper functions from the PROscorerTools package, and users are encouraged to contribute new functions to PROscorer'. More scoring functions are currently in development and will be added in future updates.

r-powerjoin 0.1.0
Propagated dependencies: r-vctrs@0.6.5 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-glue@1.8.0 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/moodymudskipper/powerjoin
Licenses: Expat
Build system: r
Synopsis: Extensions of 'dplyr' and 'fuzzyjoin' Join Functions
Description:

We extend dplyr and fuzzyjoin join functions with features to preprocess the data, apply various data checks, and deal with conflicting columns.

r-plackettluce 0.4.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://hturner.github.io/PlackettLuce/
Licenses: GPL 3
Build system: r
Synopsis: Plackett-Luce Models for Rankings
Description:

This package provides functions to prepare rankings data and fit the Plackett-Luce model jointly attributed to Plackett (1975) <doi:10.2307/2346567> and Luce (1959, ISBN:0486441369). The standard Plackett-Luce model is generalized to accommodate ties of any order in the ranking. Partial rankings, in which only a subset of items are ranked in each ranking, are also accommodated in the implementation. Disconnected/weakly connected networks implied by the rankings may be handled by adding pseudo-rankings with a hypothetical item. Optionally, a multivariate normal prior may be set on the log-worth parameters and ranker reliabilities may be incorporated as proposed by Raman and Joachims (2014) <doi:10.1145/2623330.2623654>. Maximum a posteriori estimation is used when priors are set. Methods are provided to estimate standard errors or quasi-standard errors for inference as well as to fit Plackett-Luce trees. See the package website or vignette for further details.

r-plasmamutationdetector 1.7.2
Propagated dependencies: r-variantannotation@1.56.0 r-summarizedexperiment@1.40.0 r-s4vectors@0.48.0 r-rtracklayer@1.70.0 r-rsamtools@2.26.0 r-robustbase@0.99-6 r-ggplot2@4.0.1 r-genomicranges@1.62.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PlasmaMutationDetector
Licenses: Expat
Build system: r
Synopsis: Tumor Mutation Detection in Plasma
Description:

Aims at detecting single nucleotide variation (SNV) and insertion/deletion (INDEL) in circulating tumor DNA (ctDNA), used as a surrogate marker for tumor, at each base position of an Next Generation Sequencing (NGS) analysis. Mutations are assessed by comparing the minor-allele frequency at each position to the measured PER in control samples.

r-plot-matrix 1.6.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/sigbertklinke/plot.matrix
Licenses: GPL 3
Build system: r
Synopsis: Visualizes a Matrix as Heatmap
Description:

Visualizes a matrix object plainly as heatmap. It provides S3 functions to plot simple matrices and loading matrices.

r-pleio 1.9
Propagated dependencies: r-rms@8.1-0 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://bioinformaticstools.mayo.edu/research/pleio/
Licenses: GPL 2+
Build system: r
Synopsis: Pleiotropy Test for Multiple Traits on a Genetic Marker
Description:

Perform tests for pleiotropy of multiple traits of various variable types on genotypes for a genetic marker.

r-ppcdt 0.2.0
Propagated dependencies: r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PPCDT
Licenses: ASL 2.0
Build system: r
Synopsis: An Optimal Subset Selection for Distributed Hypothesis Testing
Description:

In the era of big data, data redundancy and distributed characteristics present novel challenges to data analysis. This package introduces a method for estimating optimal subsets of redundant distributed data, based on PPCDT (Conjunction of Power and P-value in Distributed Settings). Leveraging PPC technology, this approach can efficiently extract valuable information from redundant distributed data and determine the optimal subset. Experimental results demonstrate that this method not only enhances data quality and utilization efficiency but also assesses its performance effectively. The philosophy of the package is described in Guo G. (2020) <doi:10.1007/s00180-020-00974-4>.

r-phytosanitarycalculator 1.1.3
Propagated dependencies: r-shiny@1.11.1 r-rmarkdown@2.30 r-htmltools@0.5.8.1 r-acceptancesampling@1.0.11
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PhytosanitaryCalculator
Licenses: GPL 3
Build system: r
Synopsis: Phytosanitary Calculator for Inspection Plans Based on Risks
Description:

This package provides a Shiny application for calculating phytosanitary inspection plans based on risks. It generates a diagram of pallets in a lot, highlights the units to be sampled, and documents them based on the selected sampling method (simple random or systematic sampling).

r-pprep 0.42.3
Propagated dependencies: r-hypergeo@1.2-14
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/SamCH93/ppRep
Licenses: GPL 3
Build system: r
Synopsis: Analysis of Replication Studies using Power Priors
Description:

This package provides functionality for Bayesian analysis of replication studies using power prior approaches (Pawel et al., 2023) <doi:10.1007/s11749-023-00888-5>.

r-perregmod 4.4.3
Propagated dependencies: r-sn@2.1.1 r-readxl@1.4.5 r-expm@1.0-0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://doi.org/10.1080/03610918.2024.2314662
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Fitting Periodic Coefficients Linear Regression Models
Description:

This package provides tools for fitting periodic coefficients regression models to data where periodicity plays a crucial role. It allows users to model and analyze relationships between variables that exhibit cyclical or seasonal patterns, offering functions for estimating parameters and testing the periodicity of coefficients in linear regression models. For simple periodic coefficient regression model see Regui et al. (2024) <doi:10.1080/03610918.2024.2314662>.

r-peaxai 1.0.0
Propagated dependencies: r-rms@8.1-0 r-rminer@1.5.0 r-prroc@1.4 r-proc@1.19.0.1 r-isotone@1.1-2 r-iml@0.11.4 r-fastshap@0.1.1 r-dplyr@1.1.4 r-dear@1.5.3 r-caret@7.0-1 r-benchmarking@0.33
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/rgonzalezmoyano/PEAXAI
Licenses: GPL 3
Build system: r
Synopsis: Probabilistic Efficiency Analysis Using Explainable Artificial Intelligence
Description:

This package provides a probabilistic framework that integrates Data Envelopment Analysis (DEA) (Banker et al., 1984) <doi:10.1287/mnsc.30.9.1078> with machine learning classifiers (Kuhn, 2008) <doi:10.18637/jss.v028.i05> to estimate both the (in)efficiency status and the probability of efficiency for decision-making units. The approach trains predictive models on DEA-derived efficiency labels (Charnes et al., 1985) <doi:10.1016/0304-4076(85)90133-2>, enabling explainable artificial intelligence (XAI) workflows with global and local interpretability tools, including permutation importance (Molnar et al., 2018) <doi:10.21105/joss.00786>, Shapley value explanations (Strumbelj & Kononenko, 2014) <doi:10.1007/s10115-013-0679-x>, and sensitivity analysis (Cortez, 2011) <https://CRAN.R-project.org/package=rminer>. The framework also supports probability-threshold peer selection and counterfactual improvement recommendations for benchmarking and policy evaluation. The probabilistic efficiency framework is detailed in González-Moyano et al. (2025) "Probability-based Technical Efficiency Analysis through Machine Learning", in review for publication.

r-phenopix 2.4.5
Propagated dependencies: r-zoo@1.8-14 r-terra@1.8-86 r-strucchange@1.5-4 r-stringr@1.6.0 r-sp@2.2-0 r-raster@3.6-32 r-plyr@1.8.9 r-jpeg@0.1-11 r-iterators@1.0.14 r-gtools@3.9.5 r-foreach@1.5.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=phenopix
Licenses: GPL 2
Build system: r
Synopsis: Process Digital Images of a Vegetation Cover
Description:

This package provides a collection of functions to process digital images, depict greenness index trajectories and extract relevant phenological stages.

r-pcds 0.1.8
Propagated dependencies: r-rdpack@2.6.4 r-plotrix@3.8-13 r-plot3d@1.4.2 r-interp@1.1-6 r-gmoip@1.5.5 r-combinat@0.0-8
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pcds
Licenses: GPL 2
Build system: r
Synopsis: Proximity Catch Digraphs and Their Applications
Description:

This package contains the functions for construction and visualization of various families of the proximity catch digraphs (PCDs), see (Ceyhan (2005) ISBN:978-3-639-19063-2), for computing the graph invariants for testing the patterns of segregation and association against complete spatial randomness (CSR) or uniformity in one, two and three dimensional cases. The package also has tools for generating points from these spatial patterns. The graph invariants used in testing spatial point data are the domination number (Ceyhan (2011) <doi:10.1080/03610921003597211>) and arc density (Ceyhan et al. (2006) <doi:10.1016/j.csda.2005.03.002>; Ceyhan et al. (2007) <doi:10.1002/cjs.5550350106>). The PCD families considered are Arc-Slice PCDs, Proportional-Edge PCDs, and Central Similarity PCDs.

r-pwt9 9.1-0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pwt9
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Penn World Table (Version 9.x)
Description:

The Penn World Table 9.x (<http://www.ggdc.net/pwt/>) provides information on relative levels of income, output, inputs, and productivity for 182 countries between 1950 and 2017.

r-padr 0.6.3
Propagated dependencies: r-rlang@1.1.6 r-rcpp@1.1.0 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://edwinth.github.io/padr/
Licenses: Expat
Build system: r
Synopsis: Quickly Get Datetime Data Ready for Analysis
Description:

Transforms datetime data into a format ready for analysis. It offers two core functionalities; aggregating data to a higher level interval (thicken) and imputing records where observations were absent (pad).

r-prtree 1.0.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PRTree
Licenses: GPL 3+
Build system: r
Synopsis: Probabilistic Regression Trees
Description:

Implementation of Probabilistic Regression Trees (PRTree), providing functions for model fitting and prediction, with specific adaptations to handle missing values. The main computations are implemented in Fortran for high efficiency. The package is based on the PRTree methodology described in Alkhoury et al. (2020), "Smooth and Consistent Probabilistic Regression Trees" <https://proceedings.neurips.cc/paper_files/paper/2020/file/8289889263db4a40463e3f358bb7c7a1-Paper.pdf>. Details on the treatment of missing data and implementation aspects are presented in Prass, T.S.; Neimaier, A.S.; Pumi, G. (2025), "Handling Missing Data in Probabilistic Regression Trees: Methods and Implementation in R" <doi:10.48550/arXiv.2510.03634>.

r-plsrbeta 0.3.2
Propagated dependencies: r-plsrglm@1.6.0 r-mvtnorm@1.3-3 r-mass@7.3-65 r-formula@1.2-5 r-boot@1.3-32 r-betareg@3.2-4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://fbertran.github.io/plsRbeta/
Licenses: GPL 3
Build system: r
Synopsis: Partial Least Squares Regression for Beta Regression Models
Description:

This package provides Partial least squares Regression for (weighted) beta regression models (Bertrand 2013, <https://ojs-test.apps.ocp.math.cnrs.fr/index.php/J-SFdS/article/view/215>) and k-fold cross-validation of such models using various criteria. It allows for missing data in the explanatory variables. Bootstrap confidence intervals constructions are also available.

r-phylotop 2.1.3
Propagated dependencies: r-phylobase@0.8.12 r-nhpoisson@3.4 r-igraph@2.2.1 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://michellekendall.github.io/phyloTop/
Licenses: GPL 2
Build system: r
Synopsis: Calculating Topological Properties of Phylogenies
Description:

This package provides tools for calculating and viewing topological properties of phylogenetic trees.

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-powerbal 0.0.1.1
Propagated dependencies: r-treebalance@1.2.0 r-scales@1.4.0 r-r-utils@2.13.0 r-phytools@2.5-2 r-diversitree@0.10-1 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=poweRbal
Licenses: GPL 3+
Build system: r
Synopsis: Phylogenetic Tree Models and the Power of Tree Shape Statistics
Description:

The first goal of this package is to provide a multitude of tree models, i.e., functions that generate rooted binary trees with a given number of leaves. Second, the package allows for an easy evaluation and comparison of tree shape statistics by estimating their power to differentiate between different tree models. Please note that this R package was developed alongside the manuscript "Tree balance in phylogenetic models" by S. J. Kersting, K. Wicke, and M. Fischer (2024) <doi:10.48550/arXiv.2406.05185>, which provides further background and the respective mathematical definitions. This project was supported by the project ArtIGROW, which is a part of the WIR!-Alliance ArtIFARM â Artificial Intelligence in Farming funded by the German Federal Ministry of Education and Research (No. 03WIR4805).

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