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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-pprl 0.3.9
Propagated dependencies: r-settings@0.2.7 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=PPRL
Licenses: GPL 3
Build system: r
Synopsis: Privacy Preserving Record Linkage
Description:

This package provides a toolbox for deterministic, probabilistic and privacy-preserving record linkage techniques. Combines the functionality of the Merge ToolBox (<https://www.record-linkage.de>) with current privacy-preserving techniques.

r-penic 1.0.0
Propagated dependencies: r-numderiv@2016.8-1.1 r-matrix@1.7-4 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=PenIC
Licenses: GPL 2+
Build system: r
Synopsis: Semiparametric Regression Analysis of Interval-Censored Data using Penalized Splines
Description:

Currently incorporate the generalized odds-rate model (a type of linear transformation model) for interval-censored data based on penalized monotonic B-Spline. More methods under other semiparametric models such as cure model or additive model will be included in future versions. For more details see Lu, M., Liu, Y., Li, C. and Sun, J. (2019) <arXiv:1912.11703>.

r-pcl 1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PCL
Licenses: GPL 2+
Build system: r
Synopsis: Proximal Causal Learning
Description:

We fit causal models using proxies. We implement two stage proximal least squares estimator. E.J. Tchetgen Tchetgen, A. Ying, Y. Cui, X. Shi, and W. Miao. (2020). An Introduction to Proximal Causal Learning. arXiv e-prints, arXiv-2009 <arXiv:2009.10982>.

r-pdr 1.9.4
Propagated dependencies: r-uroot@2.1-3 r-plm@2.6-7 r-pglm@0.2-4 r-lme4@1.1-37 r-glmmtmb@1.1.13
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pdR
Licenses: GPL 2+
Build system: r
Synopsis: Threshold Model and Unit Root Tests in Cross-Section and Time Series Data
Description:

Threshold model, panel version of Hylleberg et al. (1990) <DOI:10.1016/0304-4076(90)90080-D> seasonal unit root tests, and panel unit root test of Chang (2002) <DOI:10.1016/S0304-4076(02)00095-7>.

r-pptcirc 0.2.3
Propagated dependencies: r-progress@1.2.3 r-circular@0.5-2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/Karlampm/PPTcirc
Licenses: GPL 3
Build system: r
Synopsis: Projected Polya Tree for Circular Data
Description:

This package provides functionality for the prior and posterior projected Polya tree for the analysis of circular data (Nieto-Barajas and Nunez-Antonio (2019) <arXiv:1902.06020>).

r-predfairness 0.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=predfairness
Licenses: GPL 2+
Build system: r
Synopsis: Discrimination Mitigation for Machine Learning Models
Description:

Based on different statistical definitions of discrimination, several methods have been proposed to detect and mitigate social inequality in machine learning models. This package aims to provide an alternative to fairness treatment in predictive models. The ROC method implemented in this package is described by Kamiran, Karim and Zhang (2012) <https://ieeexplore.ieee.org/document/6413831/>.

r-pmevapotranspiration 0.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PMEvapotranspiration
Licenses: GPL 3
Build system: r
Synopsis: Calculation of the Penman-Monteith Evapotranspiration using Weather Variables
Description:

The Food and Agriculture Organization-56 Penman-Monteith is one of the important method for estimating evapotranspiration from vegetated land areas. This package helps to calculate reference evapotranspiration using the weather variables collected from weather station. Evapotranspiration is the process of water transfer from the land surface to the atmosphere through evaporation from soil and other surfaces and transpiration from plants. The package aims to support agricultural, hydrological, and environmental research by offering accurate and accessible reference evapotranspiration calculation. This package has been developed using concept of Córdova et al. (2015)<doi:10.1016/j.apm.2022.09.004> and Debnath et al. (2015) <doi:10.1007/s40710-015-0107-1>.

r-pv3rs 1.0.0
Propagated dependencies: r-rcolorbrewer@1.1-3 r-purrr@1.2.0 r-partitions@1.10-9 r-multicool@1.0.1 r-matrixstats@1.5.0 r-igraph@2.2.1 r-fields@17.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://aimeertaylor.github.io/Pv3Rs/
Licenses: GPL 3+
Build system: r
Synopsis: Estimate the Cause of Recurrent Vivax Malaria using Genetic Data
Description:

Plot malaria parasite genetic data on two or more episodes. Compute per-person posterior probabilities that each Plasmodium vivax (Pv) recurrence is a recrudescence, relapse, or reinfection (3Rs) using per-person P. vivax genetic data on two or more episodes and a statistical model described in Taylor, Foo and White (2022) <doi:10.1101/2022.11.23.22282669>. Plot per-recurrence posterior probabilities.

r-pagfl 1.1.4
Propagated dependencies: r-rcppthread@2.2.0 r-rcppparallel@5.1.11-1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-lifecycle@1.0.4 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/Paul-Haimerl/PAGFL
Licenses: AGPL 3+
Build system: r
Synopsis: Joint Estimation of Latent Groups and Group-Specific Coefficients in (Time-Varying) Panel Data Models
Description:

Latent group structures are a common challenge in panel data analysis. Disregarding group-level heterogeneity can introduce bias. Conversely, estimating individual coefficients for each cross-sectional unit is inefficient and may lead to high uncertainty. This package addresses the issue of unobservable group structures by implementing the pairwise adaptive group fused Lasso (PAGFL) by Mehrabani (2023) <doi:10.1016/j.jeconom.2022.12.002>. PAGFL identifies latent group structures and group-specific coefficients in a single step. On top of that, we extend the PAGFL to time-varying coefficient functions (FUSE-TIME), following Haimerl et al. (2025) <doi:10.48550/arXiv.2503.23165>.

r-pubchem-bio 1.0.5
Propagated dependencies: r-stringr@1.6.0 r-rsqlite@2.4.4 r-rcdk@3.8.2 r-r-utils@2.13.0 r-metabocoreutils@1.18.1 r-magrittr@2.0.4 r-foreach@1.5.2 r-dplyr@1.1.4 r-doparallel@1.0.17 r-data-table@1.17.8 r-curl@7.0.0 r-chnosz@2.2.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pubchem.bio
Licenses: GPL 3
Build system: r
Synopsis: Biologically Informed Metabolomic Libraries from 'PubChem'
Description:

All PubChem compounds are downloaded to a local computer, but for each compound, only partial records are used. The data are organized into small files referenced by PubChem CID. This package also contains functions to parse the biologically relevant compounds from all PubChem compounds, using biological database sources, pathway presence, and taxonomic relationships. Taxonomy is used to generate a lowest common ancestor taxonomy ID (NCBI) for each biological metabolite, which then enables creation of taxonomically specific metabolome databases for any taxon.

r-pfica 0.1.3
Propagated dependencies: r-whitening@1.4.0 r-fda@6.3.0 r-expm@1.0-0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/m-vidal/pfica
Licenses: GPL 2+
Build system: r
Synopsis: Independent Components Analysis Techniques for Functional Data
Description:

This package performs smoothed (and non-smoothed) principal/independent components analysis of functional data. Various functional pre-whitening approaches are implemented as discussed in Vidal and Aguilera (2022) â Novel whitening approaches in functional settings", <doi:10.1002/sta4.516>. Further whitening representations of functional data can be derived in terms of a few principal components, providing an avenue to explore hidden structures in low dimensional settings: see Vidal, Rosso and Aguilera (2021) â Bi-smoothed functional independent component analysis for EEG artifact removalâ , <doi:10.3390/math9111243>.

r-peaksegdp 2024.1.24
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/tdhock/PeakSegDP
Licenses: GPL 3
Build system: r
Synopsis: Dynamic Programming Algorithm for Peak Detection in ChIP-Seq Data
Description:

This package provides a quadratic time dynamic programming algorithm can be used to compute an approximate solution to the problem of finding the most likely changepoints with respect to the Poisson likelihood, subject to a constraint on the number of segments, and the changes which must alternate: up, down, up, down, etc. For more info read <http://proceedings.mlr.press/v37/hocking15.html> "PeakSeg: constrained optimal segmentation and supervised penalty learning for peak detection in count data" by TD Hocking et al, proceedings of ICML2015.

r-pawscore 1.0.3
Propagated dependencies: r-signal@1.8-1 r-brglm2@1.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pawscore
Licenses: GPL 3
Build system: r
Synopsis: Pain Assessment at Withdrawal Speeds (PAWS)
Description:

Automated pain scoring from paw withdrawal tracking data. Based on Jones et al. (2020) "A machine-vision approach for automated pain measurement at millisecond timescales" <doi:10.7554/eLife.57258>.

r-pogit 1.3.0
Propagated dependencies: r-plyr@1.8.9 r-logistf@1.26.1 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=pogit
Licenses: GPL 2
Build system: r
Synopsis: Bayesian Variable Selection for a Poisson-Logistic Model
Description:

Bayesian variable selection for regression models of under-reported count data as well as for (overdispersed) Poisson, negative binomal and binomial logit regression models using spike and slab priors.

r-petrinetr 0.3.0
Propagated dependencies: r-xml2@1.5.0 r-visnetwork@2.1.4 r-purrr@1.2.0 r-lifecycle@1.0.4 r-dplyr@1.1.4 r-diagrammer@1.0.11
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://bupar.net
Licenses: GPL 3
Build system: r
Synopsis: Building, Visualizing, Exporting and Replaying Petri Nets
Description:

This package provides functions for the construction of Petri Nets. Petri Nets can be replayed by firing enabled transitions. Silent transitions will be hidden by the execution handler. Also includes functionalities for the visualization of Petri Nets and export of Petri Nets to PNML (Petri Net Markup Language) files.

r-polyaaeppli 2.0.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=polyaAeppli
Licenses: GPL 2+
Build system: r
Synopsis: Implementation of the Polya-Aeppli Distribution
Description:

This package provides functions for evaluating the mass density, cumulative distribution function, quantile function and random variate generation for the Polya-Aeppli distribution, also known as the geometric compound Poisson distribution. More information on the implementation can be found at Conrad J. Burden (2014) <arXiv:1406.2780>.

r-pwr2ppl 0.6.0
Propagated dependencies: r-tidyr@1.3.1 r-semtools@0.5-7 r-quantreg@6.1 r-pls@2.8-5 r-phia@0.3-2 r-nlme@3.1-168 r-mbess@4.9.41 r-mass@7.3-65 r-lmtest@0.9-40 r-lmperm@2.1.6 r-lavaan@0.6-20 r-dplyr@1.1.4 r-car@3.1-3 r-broom@1.0.10 r-afex@1.5-0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pwr2ppl
Licenses: GPL 2+
Build system: r
Synopsis: Power Analyses for Common Designs (Power to the People)
Description:

Statistical power analysis for designs including t-tests, correlations, multiple regression, ANOVA, mediation, and logistic regression. Functions accompany Aberson (2019) <doi:10.4324/9781315171500>.

r-prothmm 0.1.1
Propagated dependencies: r-phontools@0.2-2.2 r-gtools@3.9.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://semran9.github.io/protHMM/
Licenses: GPL 3+
Build system: r
Synopsis: Protein Feature Extraction from Profile Hidden Markov Models
Description:

Calculates a comprehensive list of features from profile hidden Markov models (HMMs) of proteins. Adapts and ports features for use with HMMs instead of Position Specific Scoring Matrices, in order to take advantage of more accurate multiple sequence alignment by programs such as HHBlits Remmert et al. (2012) <DOI:10.1038/nmeth.1818> and HMMer Eddy (2011) <DOI:10.1371/journal.pcbi.1002195>. Features calculated by this package can be used for protein fold classification, protein structural class prediction, sub-cellular localization and protein-protein interaction, among other tasks. Some examples of features extracted are found in Song et al. (2018) <DOI:10.3390/app8010089>, Jin & Zhu (2021) <DOI:10.1155/2021/8629776>, Lyons et al. (2015) <DOI:10.1109/tnb.2015.2457906> and Saini et al. (2015) <DOI:10.1016/j.jtbi.2015.05.030>.

r-pack 0.1-2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pack
Licenses: GPL 3
Build system: r
Synopsis: Convert Values to/from Raw Vectors
Description:

This package provides functions to easily convert data to binary formats other programs/machines can understand.

r-pakpc 0.3.0
Propagated dependencies: r-shinydashboardplus@2.0.6 r-shinydashboard@0.7.3 r-shiny@1.11.1 r-rpivottable@0.3.0 r-pakpc2023@0.2.0 r-pakpc2017@1.0.0 r-magrittr@2.0.4 r-htmltools@0.5.8.1 r-dt@0.34.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PakPC
Licenses: GPL 3
Build system: r
Synopsis: 'shiny' App to Analyze Pakistan's Population Census Data
Description:

This package provides tools for analyzing Pakistan's Population Censuses data via the PakPC2023 and PakPC2017 R packages. Designed for researchers, policymakers, and professionals, the app enables in-depth numerical and graphical analysis, including detailed cross-tabulations and insights. With diverse statistical models and visualization options, it supports informed decision-making in social and economic policy. This tool enhances users ability to explore and interpret census data, providing valuable insights for effective planning and analysis across various fields.

r-proton 1.0
Propagated dependencies: r-digest@0.6.39
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=proton
Licenses: GPL 2
Build system: r
Synopsis: The Proton Game
Description:

The Proton Game is a console-based data-crunching game for younger and older data scientists. Act as a data-hacker and find Slawomir Pietraszko's credentials to the Proton server. You have to solve four data-based puzzles to find the login and password. There are many ways to solve these puzzles. You may use loops, data filtering, ordering, aggregation or other tools. Only basics knowledge of R is required to play the game, yet the more functions you know, the more approaches you can try. The knowledge of dplyr is not required but may be very helpful. This game is linked with the ,,Pietraszko's Cave story available at http://biecek.pl/BetaBit/Warsaw. It's a part of Beta and Bit series. You will find more about the Beta and Bit series at http://biecek.pl/BetaBit.

r-panalysis 2.0
Propagated dependencies: r-ggplot2@4.0.1 r-coin@1.4-3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pAnalysis
Licenses: GPL 2
Build system: r
Synopsis: Benchmarking and Rescaling R2 using Noise Percentile Analysis
Description:

This package provides the tools needed to benchmark the R2 value corresponding to a certain acceptable noise level while also providing a rescaling function based on that noise level yielding a new value of R2 we refer to as R2k which is independent of both the number of degrees of freedom and the noise distribution function.

r-picbayes 1.0
Propagated dependencies: r-survival@3.8-3 r-mcmcpack@1.7-1 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PICBayes
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Models for Partly Interval-Censored Data
Description:

This package contains functions to fit proportional hazards (PH) model to partly interval-censored (PIC) data (Pan et al. (2020) <doi:10.1177/0962280220921552>), PH model with spatial frailty to spatially dependent PIC data (Pan and Cai (2021) <doi:10.1080/03610918.2020.1839497>), and mixed effects PH model to clustered PIC data. Each random intercept/random effect can follow both a normal prior and a Dirichlet process mixture prior. It also includes the corresponding functions for general interval-censored data.

r-pvaluefunctions 1.6.3
Propagated dependencies: r-zipfr@0.6-70 r-scales@1.4.0 r-pracma@2.4.6 r-gsl@2.1-9 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/DInfanger/pvaluefunctions
Licenses: GPL 3
Build system: r
Synopsis: Creates and Plots P-Value Functions, S-Value Functions, Confidence Distributions and Confidence Densities
Description:

This package contains functions to compute and plot confidence distributions, confidence densities, p-value functions and s-value (surprisal) functions for several commonly used estimates. Instead of just calculating one p-value and one confidence interval, p-value functions display p-values and confidence intervals for many levels thereby allowing to gauge the compatibility of several parameter values with the data. These methods are discussed by Infanger D, Schmidt-Trucksäss A. (2019) <doi:10.1002/sim.8293>; Poole C. (1987) <doi:10.2105/AJPH.77.2.195>; Schweder T, Hjort NL. (2002) <doi:10.1111/1467-9469.00285>; Bender R, Berg G, Zeeb H. (2005) <doi:10.1002/bimj.200410104> ; Singh K, Xie M, Strawderman WE. (2007) <doi:10.1214/074921707000000102>; Rothman KJ, Greenland S, Lash TL. (2008, ISBN:9781451190052); Amrhein V, Trafimow D, Greenland S. (2019) <doi:10.1080/00031305.2018.1543137>; Greenland S. (2019) <doi:10.1080/00031305.2018.1529625> and Rafi Z, Greenland S. (2020) <doi:10.1186/s12874-020-01105-9>.

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