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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-vaxiner 0.1.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-scales@1.4.0 r-purrr@1.2.0 r-openxlsx@4.2.8.1 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://cran.r-project.org/package=vaxineR
Licenses: GPL 3+
Build system: r
Synopsis: Vaccine Coverage and Outbreak Risk Analysis
Description:

This package provides tools to analyze vaccine coverage data and simulate potential disease outbreak scenarios. It allows users to calculate key epidemiological metrics such as the effective reproduction number (Re), outbreak probabilities, and expected infection counts based on county-level vaccination rates, disease characteristics, and vaccine effectiveness. The package includes historical kindergarten vaccination data for Florida counties and offers functions for generating summary tables, visualizations, and exporting the underlying plot data.

r-vazul 1.1.0
Propagated dependencies: r-tidyselect@1.2.1 r-rlang@1.1.6 r-lifecycle@1.0.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://nthun.github.io/vazul/
Licenses: Expat
Build system: r
Synopsis: Analysis Blinding Tools
Description:

This package provides tools for analysis blinding in confirmatory research contexts by masking and scrambling test-relevant aspects of data. Vector-, data frame-, and row-wise operations support blinding for hierarchical and repeated-measures designs. For more details see MacCoun and Perlmutter (2015) <doi:10.1038/526187a> and Dutilh, Sarafoglou, and Wagenmakers (2019) <doi:10.1007/s11229-019-02456-7>.

r-vaultr 1.2.0
Propagated dependencies: r-r6@2.6.1 r-jsonlite@2.0.0 r-httr@1.4.7 r-getpass@0.2-4
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/vimc/vaultr
Licenses: Expat
Build system: r
Synopsis: Vault Client for Secrets and Sensitive Data
Description:

This package provides an interface to a HashiCorp vault server over its http API (typically these are self-hosted; see <https://www.vaultproject.io>). This allows for secure storage and retrieval of secrets over a network, such as tokens, passwords and certificates. Authentication with vault is supported through several backends including user name/password and authentication via GitHub'.

r-vowels 1.2-3
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://lingtools.uoregon.edu/norm/
Licenses: GPL 3
Build system: r
Synopsis: Vowel Manipulation, Normalization, and Plotting
Description:

Procedures for the manipulation, normalization, and plotting of phonetic and sociophonetic vowel formant data. vowels is the backend for the NORM website.

r-voicer 0.1.0
Propagated dependencies: r-xfun@0.54 r-tuner@1.4.7 r-stringr@1.6.0 r-soundgen@2.8.0 r-shinyjs@2.1.0 r-shinyfiles@0.9.3 r-shiny@1.11.1 r-seewave@2.2.4 r-rmarkdown@2.30 r-rlang@1.1.6 r-rcompanion@2.5.2 r-plotly@4.11.0 r-phia@0.3-2 r-mass@7.3-65 r-knitr@1.50 r-kableextra@1.4.0 r-gtable@0.3.6 r-gridextra@2.3 r-ggthemes@5.1.0 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-fsa@0.10.0 r-foreach@1.5.2 r-dt@0.34.0 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://cran.r-project.org/package=voiceR
Licenses: GPL 2
Build system: r
Synopsis: Voice Analytics for Social Scientists
Description:

Simplifies and largely automates practical voice analytics for social science research. This package offers an accessible and easy-to-use interface, including an interactive Shiny app, that simplifies the processing, extraction, analysis, and reporting of voice recording data in the behavioral and social sciences. The package includes batch processing capabilities to read and analyze multiple voice files in parallel, automates the extraction of key vocal features for further analysis, and automatically generates APA formatted reports for typical between-group comparisons in experimental social science research. A more extensive methodological introduction that inspired the development of the voiceR package is provided in Hildebrand et al. 2020 <doi:10.1016/j.jbusres.2020.09.020>.

r-vca 1.5.2
Propagated dependencies: r-numderiv@2016.8-1.1 r-matrix@1.7-4 r-lme4@1.1-37
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://cran.r-project.org/package=VCA
Licenses: GPL 3+
Build system: r
Synopsis: Variance Component Analysis
Description:

ANOVA and REML estimation of linear mixed models is implemented, once following Searle et al. (1991, ANOVA for unbalanced data), once making use of the lme4 package. The primary objective of this package is to perform a variance component analysis (VCA) according to CLSI EP05-A3 guideline "Evaluation of Precision of Quantitative Measurement Procedures" (2014). There are plotting methods for visualization of an experimental design, plotting random effects and residuals. For ANOVA type estimation two methods for computing ANOVA mean squares are implemented (SWEEP and quadratic forms). The covariance matrix of variance components can be derived, which is used in estimating confidence intervals. Linear hypotheses of fixed effects and LS means can be computed. LS means can be computed at specific values of covariables and with custom weighting schemes for factor variables. See ?VCA for a more comprehensive description of the features.

r-vic5 0.2.6
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-lubridate@1.9.4 r-foreach@1.5.2
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/rpkgs/VIC5
Licenses: GPL 3
Build system: r
Synopsis: The Variable Infiltration Capacity (VIC) Hydrological Model
Description:

The Variable Infiltration Capacity (VIC) model is a macroscale hydrologic model that solves full water and energy balances, originally developed by Xu Liang at the University of Washington (UW). The version of VIC source code used is of 5.0.1 on <https://github.com/UW-Hydro/VIC/>, see Hamman et al. (2018). Development and maintenance of the current official version of the VIC model at present is led by the UW Hydro (Computational Hydrology group) in the Department of Civil and Environmental Engineering at UW. VIC is a research model and in its various forms it has been applied to most of the major river basins around the world, as well as globally <http://vic.readthedocs.io/en/master/Documentation/References/>. References: "Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges (1994), A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res., 99(D7), 14415-14428, <doi:10.1029/94JD00483>"; "Hamman, J. J., Nijssen, B., Bohn, T. J., Gergel, D. R., and Mao, Y. (2018), The Variable Infiltration Capacity model version 5 (VIC-5): infrastructure improvements for new applications and reproducibility, Geosci. Model Dev., 11, 3481-3496, <doi:10.5194/gmd-11-3481-2018>".

r-vuer 0.6.0
Propagated dependencies: r-htmlwidgets@1.6.4 r-htmltools@0.5.8.1
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/vue-r/vueR
Licenses: Expat
Build system: r
Synopsis: 'Vuejs' Helpers and 'Htmlwidget'
Description:

Make it easy to use vue in R with helper dependency functions and examples.

r-valottery 0.0.1
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://cran.r-project.org/package=valottery
Licenses: CC0
Build system: r
Synopsis: Results from the Virginia Lottery Draw Games
Description:

Historical results for the state of Virginia lottery draw games. Data were downloaded from https://www.valottery.com/.

r-voigt 2.0
Propagated dependencies: r-pracma@2.4.6 r-invgamma@1.2 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://cran.r-project.org/package=voigt
Licenses: GPL 2
Build system: r
Synopsis: The Voigt Distribution
Description:

Random generation, density function and parameter estimation for the Voigt distribution. The main objective of this package is to provide R users with efficient estimation of Voigt parameters using classic iid data in a Bayesian framework. The estimating function allows flexible prior specification, specification of fixed parameters and several options for Markov Chain Monte Carlo posterior simulation. A basic version of the algorithm is described in: Cannas M. and Piras, N. (2025) <doi:10.1007/978-3-031-96303-2_53>.

r-vermeulen 0.1.2
Propagated dependencies: r-memoise@2.0.1
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/ramiromagno/vermeulen
Licenses: FSDG-compatible
Build system: r
Synopsis: Biomarker Data Set by Vermeulen et al. (2009)
Description:

The biomarker data set by Vermeulen et al. (2009) <doi:10.1016/S1470-2045(09)70154-8> is provided. The data source, however, is by Ruijter et al. (2013) <doi:10.1016/j.ymeth.2012.08.011>. The original data set may be downloaded from <https://medischebiologie.nl/wp-content/uploads/2019/02/qpcrdatamethods.zip>. This data set is for a real-time quantitative polymerase chain reaction (PCR) experiment that comprises the raw fluorescence data of 24,576 amplification curves. This data set comprises 59 genes of interest and 5 reference genes. Each gene was assessed on 366 neuroblastoma complementary DNA (cDNA) samples and on 18 standard dilution series samples (10-fold 5-point dilution series x 3 replicates + no template controls (NTC) x 3 replicates).

r-vscc 0.8
Propagated dependencies: r-teigen@2.2.2 r-mixghd@2.3.7 r-mclust@6.1.2 r-manlymix@0.1.15.1
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://cran.r-project.org/package=vscc
Licenses: GPL 2+
Build system: r
Synopsis: Variable Selection for Clustering and Classification
Description:

This package performs variable selection/feature reduction under a clustering or classification framework. In particular, it can be used in an automated fashion using mixture model-based methods ('teigen and mclust are currently supported). Can account for mixtures of non-Gaussian distributions via Manly transform (via ManlyMix'). See Andrews and McNicholas (2014) <doi:10.1007/s00357-013-9139-2> and Neal and McNicholas (2023) <doi:10.48550/arXiv.2305.16464>.

r-votesmart 0.1.2
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-snakecase@0.11.1 r-purrr@1.2.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-glue@1.8.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/decktools/votesmart/
Licenses: Expat
Build system: r
Synopsis: Wrapper for the Project 'VoteSmart' API
Description:

An R interface to the Project VoteSmart'<https://justfacts.votesmart.org/> API.

r-vegindexcalc 0.1.0
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://cran.r-project.org/package=vegIndexCalc
Licenses: GPL 3
Build system: r
Synopsis: Vegetation Indices (VIs) Calculation for Remote Sensing Analysis
Description:

It provides a comprehensive toolkit for calculating a suite of common vegetation indices (VIs) derived from remote sensing imagery. VIs are essential tools used to quantify vegetation characteristics, such as biomass, leaf area index (LAI) and photosynthetic activity, which are essential parameters in various ecological, agricultural, and environmental studies. Applications of this package include biomass estimation, crop monitoring, forest management, land use and land cover change analysis and climate change studies. For method details see, Deb,D.,Deb,S.,Chakraborty,D.,Singh,J.P.,Singh,A.K.,Dutta,P.and Choudhury,A.(2020)<doi:10.1080/10106049.2020.1756461>. Utilizing this R package, users can effectively extract and analyze critical information from remote sensing imagery, enhancing their comprehension of vegetation dynamics and their importance in global ecosystems. The package includes the function vegetation_indices().

r-vigicaen 1.0.0
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-rlang@1.1.6 r-purrr@1.2.0 r-lifecycle@1.0.4 r-gridextra@2.3 r-glue@1.8.0 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-data-table@1.17.8 r-cli@3.6.5 r-arrow@22.0.0
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/pharmacologie-caen/vigicaen
Licenses: FSDG-compatible
Build system: r
Synopsis: 'VigiBase' Pharmacovigilance Database Toolbox
Description:

Perform the analysis of the World Health Organization (WHO) Pharmacovigilance database VigiBase (Extract Case Level version), <https://who-umc.org/> e.g., load data, perform data management, disproportionality analysis, and descriptive statistics. Intended for pharmacovigilance routine use or studies. This package is NOT supported nor reflect the opinion of the WHO, or the Uppsala Monitoring Centre. Disproportionality methods are described by Norén et al (2013) <doi:10.1177/0962280211403604>.

r-viewpipesteps 0.1.0
Propagated dependencies: r-tibble@3.3.0 r-rstudioapi@0.17.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://cran.r-project.org/package=ViewPipeSteps
Licenses: Expat
Build system: r
Synopsis: Create View Tabs of Pipe Chains
Description:

Debugging pipe chains often consists of viewing the output after each step. This package adds RStudio addins and two functions that allow outputing each or select steps in a convenient way.

r-volumodel 0.2.3
Propagated dependencies: r-viridislite@0.4.2 r-terra@1.8-86 r-sf@1.0-23 r-rnaturalearth@1.1.0 r-rangebuilder@2.2 r-modeva@3.41 r-metr@0.18.3 r-ggtext@0.1.2 r-ggplot2@4.0.1 r-fields@17.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://hannahlowens.github.io/voluModel/
Licenses: GPL 3
Build system: r
Synopsis: Modeling Species Distributions in Three Dimensions
Description:

Facilitates modeling species ecological niches and geographic distributions based on occurrences and environments that have a vertical as well as horizontal component, and projecting models into three-dimensional geographic space. Working in three dimensions is useful in an aquatic context when the organisms one wishes to model can be found across a wide range of depths in the water column. The package also contains functions to automatically generate marine training model training regions using machine learning, and interpolate and smooth patchily sampled environmental rasters using thin plate splines. Davis Rabosky AR, Cox CL, Rabosky DL, Title PO, Holmes IA, Feldman A, McGuire JA (2016) <doi:10.1038/ncomms11484>. Nychka D, Furrer R, Paige J, Sain S (2021) <doi:10.5065/D6W957CT>. Pateiro-Lopez B, Rodriguez-Casal A (2022) <https://CRAN.R-project.org/package=alphahull>.

r-vwline 0.2-4
Propagated dependencies: r-polyclip@1.10-7 r-gridbezier@1.1-1
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/pmur002/vwline
Licenses: GPL 2+
Build system: r
Synopsis: Draw Variable-Width Lines
Description:

This package provides R functions to draw lines and curves with the width of the curve allowed to vary along the length of the curve.

r-vvmover 1.6.0
Propagated dependencies: r-readxl@1.4.5 r-readr@2.1.6 r-magrittr@2.0.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://vusaverse.github.io/vvmover/
Licenses: Expat
Build system: r
Synopsis: Read and Write Data
Description:

Offers a wide range of functions for reading and writing data in various file formats, including CSV, RDS, Excel and ZIP files. Additionally, it provides functions for retrieving metadata associated with files, such as file size and creation date, making it easy to manage and organize large data sets. This package is designed to simplify data import and export tasks, and provide users with a comprehensive set of tools to work with different types of data files.

r-visstatistics 0.1.7
Propagated dependencies: r-vcd@1.4-13 r-nortest@1.0-4 r-multcompview@0.1-10 r-cairo@1.7-0
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/shhschilling/visStatistics
Licenses: Expat
Build system: r
Synopsis: Automated Selection and Visualisation of Statistical Hypothesis Tests
Description:

Automatically selects and visualises statistical hypothesis tests between two vectors, based on their class, distribution, sample size, and a user-defined confidence level (conf.level). Visual outputs - including box plots, bar charts, regression lines with confidence bands, mosaic plots, residual plots, and Q-Q plots - are annotated with relevant test statistics, assumption checks, and post-hoc analyses where applicable. The algorithmic workflow helps the user focus on the interpretation of test results rather than test selection. It is particularly suited for quick data analysis, e.g., in statistical consulting projects or educational settings. The test selection algorithm proceeds as follows: Input vectors of class numeric or integer are considered numerical; those of class factor are considered categorical. Assumptions of residual normality and homogeneity of variances are considered met if the corresponding test yields a p-value greater than the significance level alpha = 1 - conf.level. (1) When the response vector is numerical and the predictor vector is categorical, a test of central tendencies is selected. If the categorical predictor has exactly two levels, t.test() is applied when group sizes exceed 30 (Lumley et al. (2002) <doi:10.1146/annurev.publhealth.23.100901.140546>). For smaller samples, normality of residuals is tested using shapiro.test(); if met, t.test() is used; otherwise, wilcox.test(). If the predictor is categorical with more than two levels, an aov() is initially fitted. Residual normality is evaluated using both shapiro.test() and ad.test(); residuals are considered approximately normal if at least one test yields a p-value above alpha. If this assumption is met, bartlett.test() assesses variance homogeneity. If variances are homogeneous, aov() is used; otherwise oneway.test(). Both tests are followed by TukeyHSD(). If residual normality cannot be assumed, kruskal.test() is followed by pairwise.wilcox.test(). (2) When both the response and predictor vectors are numerical, a simple linear regression model is fitted using lm(). (3) When both vectors are categorical, Cochran's rule (Cochran (1954) <doi:10.2307/3001666>) is applied to test independence either by chisq.test() or fisher.test().

r-vvtableau 0.9.0
Propagated dependencies: r-xml2@1.5.0 r-xml@3.99-0.20 r-tidyr@1.3.1 r-stringr@1.6.0 r-purrr@1.2.0 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-dplyr@1.1.4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/vusaverse/vvtableau
Licenses: Expat
Build system: r
Synopsis: R Interface for 'Tableau' Services
Description:

This package provides an R interface for interacting with the Tableau Server. It allows users to perform various operations such as publishing workbooks, refreshing data extracts, and managing users using the Tableau REST API (see <https://help.tableau.com/current/api/rest_api/en-us/REST/rest_api_ref.htm> for details). Additionally, it includes functions to perform manipulations on local Tableau workbooks.

r-visitorcounts 2.0.3
Propagated dependencies: r-zoo@1.8-14 r-rssa@1.1 r-ggplot2@4.0.1 r-cowplot@1.2.0
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://cran.r-project.org/package=VisitorCounts
Licenses: GPL 3
Build system: r
Synopsis: Modeling and Forecasting Visitor Counts Using Social Media
Description:

This package performs modeling and forecasting of park visitor counts using social media data and (partial) on-site visitor counts. Specifically, the model is built based on an automatic decomposition of the trend and seasonal components of the social media-based park visitor counts, from which short-term forecasts of the visitor counts and percent changes in the visitor counts can be made. A reference for the underlying model that VisitorCounts uses can be found at Russell Goebel, Austin Schmaltz, Beth Ann Brackett, Spencer A. Wood, Kimihiro Noguchi (2023) <doi:10.1002/for.2965> .

r-vivaldi 1.0.1
Propagated dependencies: r-vcfr@1.15.0 r-tidyselect@1.2.1 r-tidyr@1.3.1 r-seqinr@4.2-36 r-plotly@4.11.0 r-magrittr@2.0.4 r-glue@1.8.0 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/GreshamLab/vivaldi
Licenses: Expat
Build system: r
Synopsis: Viral Variant Location and Diversity
Description:

Analysis of minor alleles in Illumina sequencing data of viral genomes. Functions in vivaldi primarily operate on vcf files.

r-valytics 0.4.0
Propagated dependencies: r-robslopes@1.1.3 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/marcellogr/valytics
Licenses: GPL 3
Build system: r
Synopsis: Statistical Methods for Analytical Method Comparison and Validation
Description:

This package provides statistical methods for analytical method comparison and validation studies. Implements Bland-Altman analysis for assessing agreement between measurement methods (Bland & Altman (1986) <doi:10.1016/S0140-6736(86)90837-8>), Passing-Bablok regression for non-parametric method comparison (Passing & Bablok (1983) <doi:10.1515/cclm.1983.21.11.709>), and Deming regression accounting for measurement error in both variables (Linnet (1993) <doi:10.1093/clinchem/39.3.424>). Also includes tools for setting quality goals based on biological variation (Fraser & Petersen (1993) <doi:10.1093/clinchem/39.7.1447>) and calculating Six Sigma metrics, precision experiments with variance component analysis, precision profiles for functional sensitivity estimation (Kroll & Emancipator (1993) <https://pubmed.ncbi.nlm.nih.gov/8448849/>). Commonly used in clinical laboratory method validation. Provides publication-ready plots and comprehensive statistical summaries.

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