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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-allspicer 0.1.9
Propagated dependencies: r-readr@2.1.6 r-mvtnorm@1.3-3 r-magrittr@2.0.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=ALLSPICER
Licenses: Expat
Build system: r
Synopsis: ALLelic Spectrum of Pleiotropy Informed Correlated Effects
Description:

This package provides statistical tools to analyze heterogeneous effects of rare variants within genes that are associated with multiple traits. The package implements methods for assessing pleiotropic effects and identifying allelic heterogeneity, which can be useful in large-scale genetic studies. Methods include likelihood-based statistical tests to assess these effects. For more details, see Lu et al. (2024) <doi:10.1101/2024.10.01.614806>.

r-albi 0.1.9
Propagated dependencies: r-openxlsx@4.2.8.1 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/Ataher76/aLBI
Licenses: GPL 3
Build system: r
Synopsis: Estimating Length-Based Indicators for Fish Stock
Description:

This package provides tools for estimating length-based indicators from length frequency data to assess fish stock status and manage fisheries sustainably. Implements methods from Cope and Punt (2009) <doi:10.1577/C08-025.1> for data-limited stock assessment and Froese (2004) <doi:10.1111/j.1467-2979.2004.00144.x> for detecting overfishing using simple indicators. Key functions include: FrequencyTable(): Calculate the frequency table from the collected and also the extract the length frequency data from the frequency table with the upper length_range. A numeric value specifying the bin width for class intervals. If not provided, the bin width is automatically calculated using Wang (2020) <doi:10.1016/j.fishres.2019.105474> formula. FreqTM(): Creates a frequency distribution table for fish length data across multiple months using a consistent length class structure. The bin width is determined by either a custom value or Wang's formula, applied uniformly across all months. The function dynamically detects and renames columns to Month and Length from the input dataframe. The maximum observed length is included as part of the last class, with the upper bound set to the smallest multiple of the bin width greater than or equal to the maximum length. Months can be converted to dates using a configurable day and year, with dates assigned sequentially in day.month.year format (e.g., 15.01.26). FishPar(): Calculates length-based indicators (LBIs) proposed by Froese (2004) <doi:10.1111/j.1467-2979.2004.00144.x> such as the percentage of mature fish (Pmat), percentage of optimal length fish (Popt), percentage of mega spawners (Pmega), and the sum of these as Pobj. This function also estimates confidence intervals for different lengths, visualizes length frequency distributions, and provides data frames containing calculated values. FishSS(): Makes decisions based on input from Cope and Punt (2009) <doi:10.1577/C08-025.1> and parameters calculated by FishPar() (e.g., Pobj, Pmat, Popt, LM_ratio) to determine stock status as target spawning biomass (TSB40) and limit spawning biomass (LSB25), and selectivity. LWR(): Fits and visualizes length-weight relationships using linear regression, with options for log-transformation and customizable plotting.

r-autobagging 0.1.0
Propagated dependencies: r-xgboost@1.7.11.1 r-rpart@4.1.24 r-party@1.3-18 r-minerva@1.5.10 r-mass@7.3-65 r-lsr@0.5.2 r-infotheo@1.2.0.1 r-entropy@1.3.2 r-e1071@1.7-16 r-corelearn@1.57.3.1 r-cluster@2.1.8.1 r-caret@7.0-1 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=autoBagging
Licenses: GPL 2+
Build system: r
Synopsis: Learning to Rank Bagging Workflows with Metalearning
Description:

This package provides a framework for automated machine learning. Concretely, the focus is on the optimisation of bagging workflows. A bagging workflows is composed by three phases: (i) generation: which and how many predictive models to learn; (ii) pruning: after learning a set of models, the worst ones are cut off from the ensemble; and (iii) integration: how the models are combined for predicting a new observation. autoBagging optimises these processes by combining metalearning and a learning to rank approach to learn from metadata. It automatically ranks 63 bagging workflows by exploiting past performance and dataset characterization. A complete description of the method can be found in: Pinto, F., Cerqueira, V., Soares, C., Mendes-Moreira, J. (2017): "autoBagging: Learning to Rank Bagging Workflows with Metalearning" arXiv preprint arXiv:1706.09367.

r-ananke 0.1.0
Propagated dependencies: r-arkhe@1.11.0 r-aion@1.7.0
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://codeberg.org/tesselle/ananke
Licenses: GPL 3+
Build system: r
Synopsis: Quantitative Chronology in Archaeology
Description:

Simple radiocarbon calibration and chronological analysis. This package allows the calibration of radiocarbon ages and modern carbon fraction values using multiple calibration curves. It allows the calculation of highest density region intervals and credible intervals. The package also provides tools for visualising results and estimating statistical summaries.

r-autostsm 3.1.5
Propagated dependencies: r-strucchange@1.5-4 r-sandwich@3.1-1 r-progress@1.2.3 r-maxlik@1.5-2.1 r-lubridate@1.9.4 r-lmtest@0.9-40 r-kalmanfilter@2.2.0 r-gridextra@2.3 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-forecast@8.24.0 r-foreach@1.5.2 r-dosnow@1.0.20 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=autostsm
Licenses: GPL 2+
Build system: r
Synopsis: Automatic Structural Time Series Models
Description:

Automatic model selection for structural time series decomposition into trend, cycle, and seasonal components, plus optionality for structural interpolation, using the Kalman filter. Koopman, Siem Jan and Marius Ooms (2012) "Forecasting Economic Time Series Using Unobserved Components Time Series Models" <doi:10.1093/oxfordhb/9780195398649.013.0006>. Kim, Chang-Jin and Charles R. Nelson (1999) "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications" <doi:10.7551/mitpress/6444.001.0001><http://econ.korea.ac.kr/~cjkim/>.

r-arttransfer 1.0.0
Propagated dependencies: r-randomforest@4.7-1.2 r-nnet@7.3-20 r-glmnet@4.1-10 r-gbm@2.2.2
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=ARTtransfer
Licenses: GPL 2
Build system: r
Synopsis: Adaptive and Robust Pipeline for Transfer Learning
Description:

Adaptive and Robust Transfer Learning (ART) is a flexible framework for transfer learning that integrates information from auxiliary data sources to improve model performance on primary tasks. It is designed to be robust against negative transfer by including the non-transfer model in the candidate pool, ensuring stable performance even when auxiliary datasets are less informative. See the paper, Wang, Wu, and Ye (2023) <doi:10.1002/sta4.582>.

r-atlasmaker 0.1.0
Propagated dependencies: r-shiny@1.11.1 r-leaflet@2.2.3
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/rachel-greenlee/AtlasMaker
Licenses: GPL 3+
Build system: r
Synopsis: Make Multiple 'leaflet' Maps in 'Shiny'
Description:

Simplify creating multiple, related leaflet maps across tabs for a shiny application. Users build lists of any polygons, points, and polylines needed for the project, use the map_server() function to assign built lists and other chosen aesthetics into each tab, and the package leverages modules to generate all map tabs.

r-av 0.9.6
Dependencies: zlib@1.3.1
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://ropensci.r-universe.dev/av
Licenses: Expat
Build system: r
Synopsis: Working with Audio and Video in R
Description:

Bindings to FFmpeg <http://www.ffmpeg.org/> AV library for working with audio and video in R. Generates high quality video from images or R graphics with custom audio. Also offers high performance tools for reading raw audio, creating spectrograms', and converting between countless audio / video formats. This package interfaces directly to the C API and does not require any command line utilities.

r-aquaticlifehistory 1.0.6
Propagated dependencies: r-tidyr@1.3.1 r-rlist@0.4.6.2 r-readr@2.1.6 r-plyr@1.8.9 r-mumin@1.48.11 r-minpack-lm@1.2-4 r-mass@7.3-65 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-broom@1.0.10
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/jonathansmart/AquaticLifeHistory
Licenses: GPL 3
Build system: r
Synopsis: Life History Analysis Tools
Description:

Estimate aquatic species life history using robust techniques. This package supports users undertaking two types of analysis: 1) Growth from length-at-age data, and 2) maturity analyses for length and/or age data. Maturity analyses are performed using generalised linear model approaches incorporating either a binomial or quasibinomial distribution. Growth modelling is performed using the multimodel approach presented by Smart et al. (2016) "Multimodel approaches in shark and ray growth studies: strengths, weaknesses and the future" <doi:10.1111/faf.12154>.

r-aws-translate 0.1.4
Propagated dependencies: r-jsonlite@2.0.0 r-httr@1.4.7 r-aws-signature@0.6.0
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/cloudyr/aws.translate
Licenses: GPL 2+
Build system: r
Synopsis: Client for 'AWS Translate'
Description:

This package provides a client for AWS Translate <https://aws.amazon.com/documentation/translate>, a machine translation service that will convert a text input in one language into a text output in another language.

r-aphylo 0.3-6
Propagated dependencies: r-xml2@1.5.0 r-rcpp@1.1.0 r-matrix@1.7-4 r-mass@7.3-65 r-fmcmc@0.5-2 r-coda@0.19-4.1 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/USCbiostats/aphylo
Licenses: Expat
Build system: r
Synopsis: Statistical Inference and Prediction of Annotations in Phylogenetic Trees
Description:

This package implements a parsimonious evolutionary model to analyze and predict gene-functional annotations in phylogenetic trees as described in Vega Yon et al. (2021) <doi:10.1371/journal.pcbi.1007948>. Focusing on computational efficiency, aphylo makes it possible to estimate pooled phylogenetic models, including thousands (hundreds) of annotations (trees) in the same run. The package also provides the tools for visualization of annotated phylogenies, calculation of posterior probabilities (prediction) and goodness-of-fit assessment featured in Vega Yon et al. (2021).

r-arete 0.1
Propagated dependencies: r-terra@1.8-86 r-stringr@1.6.0 r-rmarkdown@2.30 r-reticulate@1.44.1 r-pdftools@3.6.0 r-kableextra@1.4.0 r-jsonlite@2.0.0 r-irr@0.84.1 r-googledrive@2.1.2 r-ggplot2@4.0.1 r-gecko@1.0.2 r-fedmatch@2.1.0 r-dplyr@1.1.4 r-cld2@1.2.6
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=arete
Licenses: GPL 3
Build system: r
Synopsis: Automated REtrieval from TExt
Description:

This package provides a Python based pipeline for extraction of species occurrence data through the usage of large language models. Includes validation tools designed to handle model hallucinations for a scientific, rigorous use of LLM. Currently supports usage of GPT with more planned, including local and non-proprietary models. For more details on the methodology used please consult the references listed under each function, such as Kent, A. et al. (1995) <doi:10.1002/asi.5090060209>, van Rijsbergen, C.J. (1979, ISBN:978-0408709293, Levenshtein, V.I. (1966) <https://nymity.ch/sybilhunting/pdf/Levenshtein1966a.pdf> and Klaus Krippendorff (2011) <https://repository.upenn.edu/handle/20.500.14332/2089>.

r-astrochron 1.5
Propagated dependencies: r-viridislite@0.4.2 r-palinsol@1.0 r-multitaper@1.0-17 r-iterators@1.0.14 r-idpmisc@1.1.21 r-foreach@1.5.2 r-fields@17.1 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=astrochron
Licenses: GPL 3
Build system: r
Synopsis: Computational Tool for Astrochronology
Description:

Routines for astrochronologic testing, astronomical time scale construction, and time series analysis <doi:10.1016/j.earscirev.2018.11.015>. Also included are a range of statistical analysis and modeling routines that are relevant to time scale development and paleoclimate analysis.

r-archidart 3.4
Propagated dependencies: r-xml@3.99-0.20 r-sp@2.2-0 r-gtools@3.9.5 r-geometry@0.5.2
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://archidart.github.io/
Licenses: GPL 2
Build system: r
Synopsis: Plant Root System Architecture Analysis Using DART and RSML Files
Description:

Analysis of complex plant root system architectures (RSA) using the output files created by Data Analysis of Root Tracings (DART), an open-access software dedicated to the study of plant root architecture and development across time series (Le Bot et al (2010) "DART: a software to analyse root system architecture and development from captured images", Plant and Soil, <DOI:10.1007/s11104-009-0005-2>), and RSA data encoded with the Root System Markup Language (RSML) (Lobet et al (2015) "Root System Markup Language: toward a unified root architecture description language", Plant Physiology, <DOI:10.1104/pp.114.253625>). More information can be found in Delory et al (2016) "archiDART: an R package for the automated computation of plant root architectural traits", Plant and Soil, <DOI:10.1007/s11104-015-2673-4>.

r-autoseed 0.1.0
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=Autoseed
Licenses: GPL 3+
Build system: r
Synopsis: Retrieve Disease-Related Genes from Public Sources
Description:

For researchers to quickly and comprehensively acquire disease genes, so as to understand the mechanism of disease, we developed this program to acquire disease-related genes. The data is integrated from three public databases. The three databases are eDGAR', DrugBank and MalaCards'. The eDGAR is a comprehensive database, containing data on the relationship between disease and genes. DrugBank contains information on 13443 drugs and 5157 targets. MalaCards integrates human disease information, including disease-related genes.

r-ade4tkgui 0.3.4
Propagated dependencies: r-lattice@0.22-7 r-adegraphics@1.0-22 r-ade4@1.7-23
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/adeverse/ade4TkGUI
Licenses: GPL 2+
Build system: r
Synopsis: 'ade4' Tcl/Tk Graphical User Interface
Description:

This package provides a Tcl/Tk GUI for some basic functions in the ade4 package.

r-asmbpls 1.0.0
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-ggpubr@0.6.2 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=asmbPLS
Licenses: GPL 2+
Build system: r
Synopsis: Predicting and Classifying Patient Phenotypes with Multi-Omics Data
Description:

Adaptive Sparse Multi-block Partial Least Square, a supervised algorithm, is an extension of the Sparse Multi-block Partial Least Square, which allows different quantiles to be used in different blocks of different partial least square components to decide the proportion of features to be retained. The best combinations of quantiles can be chosen from a set of user-defined quantiles combinations by cross-validation. By doing this, it enables us to do the feature selection for different blocks, and the selected features can then be further used to predict the outcome. For example, in biomedical applications, clinical covariates plus different types of omics data such as microbiome, metabolome, mRNA data, methylation data, copy number variation data might be predictive for patients outcome such as survival time or response to therapy. Different types of data could be put in different blocks and along with survival time to fit the model. The fitted model can then be used to predict the survival for the new samples with the corresponding clinical covariates and omics data. In addition, Adaptive Sparse Multi-block Partial Least Square Discriminant Analysis is also included, which extends Adaptive Sparse Multi-block Partial Least Square for classifying the categorical outcome.

r-aziad 0.0.3
Propagated dependencies: r-qrm@0.4-35 r-foreach@1.5.2 r-extradistr@1.10.0 r-envstats@3.1.0 r-doparallel@1.0.17 r-corpcor@1.6.10
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=AZIAD
Licenses: Expat
Build system: r
Synopsis: Analyzing Zero-Inflated and Zero-Altered Data
Description:

Description: Computes maximum likelihood estimates of general, zero-inflated, and zero-altered models for discrete and continuous distributions. It also performs Kolmogorov-Smirnov (KS) tests and likelihood ratio tests for general, zero-inflated, and zero-altered data. Additionally, it obtains the inverse of the Fisher information matrix and confidence intervals for the parameters of general, zero-inflated, and zero-altered models. The package simulates random deviates from zero-inflated or hurdle models to obtain maximum likelihood estimates. Based on the work of Aldirawi et al. (2022) <doi:10.1007/s42519-021-00230-y> and Dousti Mousavi et al. (2023) <doi:10.1080/00949655.2023.2207020>.

r-affiner 0.2.1
Propagated dependencies: r-r6@2.6.1
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://trevorldavis.com/R/affiner/
Licenses: Expat
Build system: r
Synopsis: Finer Way to Render 3D Illustrated Objects in 'grid' Using Affine Transformations
Description:

Dilate, permute, project, reflect, rotate, shear, and translate 2D and 3D points. Supports parallel projections including oblique projections such as the cabinet projection as well as axonometric projections such as the isometric projection. Use grid's "affine transformation" feature to render illustrated flat surfaces.

r-aws-transcribe 0.1.3
Propagated dependencies: r-jsonlite@2.0.0 r-httr@1.4.7 r-aws-signature@0.6.0
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/cloudyr/aws.transcribe
Licenses: GPL 2+
Build system: r
Synopsis: Client for 'AWS Transcribe'
Description:

Client for AWS Transcribe <https://aws.amazon.com/documentation/transcribe>, a cloud transcription service that can convert an audio media file in English and other languages into a text transcript.

r-aspu 1.50
Propagated dependencies: r-mvtnorm@1.3-3 r-matrixstats@1.5.0 r-mass@7.3-65 r-gee@4.13-29 r-fields@17.1
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/ikwak2/aSPU
Licenses: GPL 3
Build system: r
Synopsis: Adaptive Sum of Powered Score Test
Description:

R codes for the (adaptive) Sum of Powered Score ('SPU and aSPU') tests, inverse variance weighted Sum of Powered score ('SPUw and aSPUw') tests and gene-based and some pathway based association tests (Pathway based Sum of Powered Score tests ('SPUpath'), adaptive SPUpath ('aSPUpath') test, GEEaSPU test for multiple traits - single SNP (single nucleotide polymorphism) association in generalized estimation equations, MTaSPUs test for multiple traits - single SNP association with Genome Wide Association Studies ('GWAS') summary statistics, Gene-based Association Test that uses an extended Simes procedure ('GATES'), Hybrid Set-based Test ('HYST') and extended version of GATES test for pathway-based association testing ('GATES-Simes'). ). The tests can be used with genetic and other data sets with covariates. The response variable is binary or quantitative. Summary; (1) Single trait-'SNP set association with individual-level data ('aSPU', aSPUw', aSPUr'), (2) Single trait-'SNP set association with summary statistics ('aSPUs'), (3) Single trait-pathway association with individual-level data ('aSPUpath'), (4) Single trait-pathway association with summary statistics ('aSPUsPath'), (5) Multiple traits-single SNP association with individual-level data ('GEEaSPU'), (6) Multiple traits- single SNP association with summary statistics ('MTaSPUs'), (7) Multiple traits-'SNP set association with summary statistics('MTaSPUsSet'), (8) Multiple traits-pathway association with summary statistics('MTaSPUsSetPath').

r-aipw 0.6.9.2
Propagated dependencies: r-superlearner@2.0-29 r-rsolnp@2.0.1 r-r6@2.6.1 r-progressr@0.18.0 r-ggplot2@4.0.1 r-future-apply@1.20.0
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://github.com/yqzhong7/AIPW
Licenses: GPL 3
Build system: r
Synopsis: Augmented Inverse Probability Weighting
Description:

The AIPW package implements the augmented inverse probability weighting, a doubly robust estimator, for average causal effect estimation with user-defined stacked machine learning algorithms. To cite the AIPW package, please use: "Yongqi Zhong, Edward H. Kennedy, Lisa M. Bodnar, Ashley I. Naimi (2021). AIPW: An R Package for Augmented Inverse Probability Weighted Estimation of Average Causal Effects. American Journal of Epidemiology. <doi:10.1093/aje/kwab207>". Visit: <https://yqzhong7.github.io/AIPW/> for more information.

r-amcp 1.0.2
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://cran.r-project.org/package=AMCP
Licenses: GPL 3+
Build system: r
Synopsis: Model Comparison Perspective
Description:

Accompanies the book "Designing experiments and analyzing data: A model comparison perspective" (3rd ed.) by Maxwell, Delaney, & Kelley (2018; Routledge). Contains all of the data sets in the book's chapters and end-of-chapter exercises. Information about the book is available at <https://designingexperiments.com/>.

r-aloom 0.1.1
Propagated dependencies: r-randomforest@4.7-1.2 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/a.scm (guix-cran packages a)
Home page: https://www.rcc.org.rs/aloom.html
Licenses: GPL 2
Build system: r
Synopsis: All Leave-One-Out Models
Description:

This package creates all leave-one-out models and produces predictions for test samples.

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Total results: 21283