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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-vsp 0.1.3
Propagated dependencies: r-withr@3.0.2 r-tibble@3.3.0 r-rspectra@0.16-2 r-rlang@1.1.6 r-matrix@1.7-4 r-magrittr@2.0.4 r-lrmf3@0.1.0 r-invertiforms@0.1.2 r-glue@1.8.0 r-ggplot2@4.0.1 r-clue@0.3-66
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://rohelab.github.io/vsp/
Licenses: Expat
Build system: r
Synopsis: Vintage Sparse PCA for Semi-Parametric Factor Analysis
Description:

This package provides fast spectral estimation of latent factors in random dot product graphs using the vsp estimator. Under mild assumptions, the vsp estimator is consistent for (degree-corrected) stochastic blockmodels, (degree-corrected) mixed-membership stochastic blockmodels, and degree-corrected overlapping stochastic blockmodels.

r-vlf 1.1-3
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://cran.r-project.org/package=VLF
Licenses: GPL 3+
Build system: r
Synopsis: Frequency Matrix Approach for Assessing Very Low Frequency Variants in Sequence Records
Description:

Using frequency matrices, very low frequency variants (VLFs) are assessed for amino acid and nucleotide sequences. The VLFs are then compared to see if they occur in only one member of a species, singleton VLFs, or if they occur in multiple members of a species, shared VLFs. The amino acid and nucleotide VLFs are then compared to see if they are concordant with one another. Amino acid VLFs are also assessed to determine if they lead to a change in amino acid residue type, and potential changes to protein structures. Based on Stoeckle and Kerr (2012) <doi:10.1371/journal.pone.0043992> and Phillips et al. (2023) <doi:10.3897/BDJ.11.e96480>.

r-visualpred 0.1.2
Propagated dependencies: r-randomforest@4.7-1.2 r-proc@1.19.0.1 r-nnet@7.3-20 r-mltools@0.3.5 r-mba@0.1-2 r-mass@7.3-65 r-magrittr@2.0.4 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-gbm@2.2.2 r-factominer@2.12 r-e1071@1.7-16 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://cran.r-project.org/package=visualpred
Licenses: GPL 3+
Build system: r
Synopsis: Visualization 2D of Binary Classification Models
Description:

Visual contour and 2D point and contour plots for binary classification modeling under algorithms such as glm', rf', gbm', nnet and svm', presented over two dimensions generated by famd and mca methods. Package FactoMineR for multivariate reduction functions and package MBA for interpolation functions are used. The package can be used to visualize the discriminant power of input variables and algorithmic modeling, explore outliers, compare algorithm behaviour, etc. It has been created initially for teaching purposes, but it has also many practical uses under the XAI paradigm.

r-viscov 1.6.0
Propagated dependencies: r-trialr@0.1.6 r-scatterplot3d@0.3-44 r-kernsmooth@2.23-26 r-clustergeneration@1.3.8 r-bayesm@3.1-7
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://cran.r-project.org/package=VisCov
Licenses: GPL 3+
Build system: r
Synopsis: Visualizing of Distributions of Covariance Matrices
Description:

Visualizing of distributions of covariance matrices. The package implements the methodology described in Tokuda, T., Goodrich, B., Van Mechelen, I., Gelman, A., & Tuerlinckx, F. (2012) <https://sites.stat.columbia.edu/gelman/research/unpublished/Visualization.pdf>.

r-vetr 0.2.20
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/brodieG/vetr
Licenses: GPL 2+
Build system: r
Synopsis: Trust, but Verify
Description:

Declarative template-based framework for verifying that objects meet structural requirements, and auto-composing error messages when they do not.

r-vorteksexport 0.1.8
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://cran.r-project.org/package=VorteksExport
Licenses: GPL 3
Build system: r
Synopsis: Export Dataframes to 'Vorteks' Software
Description:

Export dataframes and automatically start importing into Vorteks'. Vorteks Visualization Environment (VVE) and Vorteks Data Manager (VDM) will start an import. Vorteks Processing Environment (VPE) will start a new project and add a file reader with the dataframe file already set. Warning: WINDOWS ONLY. Requires installation of Vorteks software.

r-valet 0.9.1
Propagated dependencies: r-readr@2.1.6 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
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/runkelcorey/valet
Licenses: Expat
Build system: r
Synopsis: Provide R Client to the Bank of Canada's Valet API
Description:

The Bank of Canada updated their Valet API <https://www.bankofcanada.ca/valet/docs>, and no R client currently exists. This provides access to all of Valet's endpoints and serves responses in wide format easy for researchers to handle but also provides tools to access API responses as a list.

r-validatesuggest 0.3.2
Propagated dependencies: r-whisker@0.4.1 r-validate@1.1.7 r-rpart@4.1.24
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/data-cleaning/validatesuggest
Licenses: Expat
Build system: r
Synopsis: Generate Suggestions for Validation Rules
Description:

Generate suggestions for validation rules from a reference data set, which can be used as a starting point for domain specific rules to be checked with package validate'.

r-visualdom 0.8.0
Propagated dependencies: r-waveslim@1.8.5 r-wavemulcor@3.1.2 r-plot3d@1.4.2
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://cran.r-project.org/package=VisualDom
Licenses: GPL 2+
Build system: r
Synopsis: Visualize Dominant Variables in Wavelet Multiple Correlation
Description:

Estimates and plots as a heat map the correlation coefficients obtained via the wavelet local multiple correlation WLMC (Fernández-Macho 2018) and the dominant variable/s, i.e., the variable/s that maximizes the multiple correlation through time and scale (Polanco-Martà nez et al. 2020, Polanco-Martà nez 2022). We improve the graphical outputs of WLMC proposing a didactic and useful way to visualize the dominant variable(s) for a set of time series. The WLMC was designed for financial time series, but other kinds of data (e.g., climatic, ecological, etc.) can be used. The functions contained in VisualDom are highly flexible since these contains several parameters to personalize the time series under analysis and the heat maps. In addition, we have also included two data sets (named rdata_climate and rdata_Lorenz') to exemplify the use of the functions contained in VisualDom'. Methods derived from Fernández-Macho (2018) <doi:10.1016/j.physa.2017.11.050>, Polanco-Martà nez et al. (2020) <doi:10.1038/s41598-020-77767-8> and Polanco-Martà nez (2023, in press).

r-vegperiod 0.4.0
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://rnuske.github.io/vegperiod/
Licenses: GPL 3+
Build system: r
Synopsis: Determine Thermal Vegetation Periods
Description:

Collection of common methods to determine growing season length in a simple manner. Start and end dates of the vegetation periods are calculated solely based on daily mean temperatures and the day of the year.

r-vvfiller 0.6.7
Propagated dependencies: r-rlang@1.1.6 r-purrr@1.2.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/vusaverse/vvfiller
Licenses: Expat
Build system: r
Synopsis: Fill Data Points
Description:

This package provides numerous functions to fill data. These can be applied either to missing or skewed data. The functions are designed within the scope of Student Analytics.

r-vsolassobag 1.0
Propagated dependencies: r-survival@3.8-3 r-summarizedexperiment@1.40.0 r-pot@1.1-11 r-pbapply@1.7-4 r-glmnet@4.1-10 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://cran.r-project.org/package=VSOLassoBag
Licenses: GPL 3
Build system: r
Synopsis: Variable Selection Oriented LASSO Bagging Algorithm
Description:

This package provides a wrapped LASSO approach by integrating an ensemble learning strategy to help select efficient, stable, and high confidential variables from omics-based data. Using a bagging strategy in combination of a parametric method or inflection point search method for cut-off threshold determination. This package can integrate and vote variables generated from multiple LASSO models to determine the optimal candidates. Luo H, Zhao Q, et al (2020) <doi:10.1126/scitranslmed.aax7533> for more details.

r-viscollin 0.1.2
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/friendly/VisCollin
Licenses: GPL 3+
Build system: r
Synopsis: Visualizing Collinearity Diagnostics
Description:

This package provides methods to calculate diagnostics for multicollinearity among predictors in a linear or generalized linear model. It also provides methods to visualize those diagnostics following Friendly & Kwan (2009), "Whereâ s Waldo: Visualizing Collinearity Diagnostics", <doi:10.1198/tast.2009.0012>. These include better tabular presentation of collinearity diagnostics that highlight the important numbers, a semi-graphic tableplot of the diagnostics to make warning and danger levels more salient, and a "collinearity biplot" of the smallest dimensions of predictor space, where collinearity is most apparent.

r-vrnmf 1.0.2
Propagated dependencies: r-quadprog@1.5-8 r-nnls@1.6 r-matrix@1.7-4 r-lpsolveapi@5.5.2.0-17.14 r-ica@1.0-3
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/kharchenkolab/vrnmf
Licenses: GPL 3
Build system: r
Synopsis: Volume-Regularized Structured Matrix Factorization
Description:

This package implements a set of routines to perform structured matrix factorization with minimum volume constraints. The NMF procedure decomposes a matrix X into a product C * D. Given conditions such that the matrix C is non-negative and has sufficiently spread columns, then volume minimization of a matrix D delivers a correct and unique, up to a scale and permutation, solution (C, D). This package provides both an implementation of volume-regularized NMF and "anchor-free" NMF, whereby the standard NMF problem is reformulated in the covariance domain. This algorithm was applied in Vladimir B. Seplyarskiy Ruslan A. Soldatov, et al. "Population sequencing data reveal a compendium of mutational processes in the human germ line". Science, 12 Aug 2021. <doi:10.1126/science.aba7408>. This package interacts with data available through the simulatedNMF package, which is available in a drat repository. To access this data package, see the instructions at <https://github.com/kharchenkolab/vrnmf>. The size of the simulatedNMF package is approximately 8 MB.

r-volcanoplot 1.0.0
Propagated dependencies: r-tidyr@1.3.1 r-shiny@1.11.1 r-purrr@1.2.0 r-ggplot2@4.0.1 r-fmsb@0.7.6 r-dt@0.34.0 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=volcanoPlot
Licenses: Expat
Build system: r
Synopsis: Volcano Plot for Clinical Trial Adverse Events
Description:

Interactive adverse event (AE) volcano plot for monitoring clinical trial safety. This tool allows users to view the overall distribution of AEs in a clinical trial using standard (e.g. MedDRA preferred term) or custom (e.g. Gender) categories using a volcano plot similar to proposal by Zink et al. (2013) <doi:10.1177/1740774513485311>. This tool provides a stand-along shiny application and flexible shiny modules allowing this tool to be used as a part of more robust safety monitoring framework like the Shiny app from the safetyGraphics R package.

r-vtable 1.4.8
Propagated dependencies: r-sjlabelled@1.2.0 r-rstudioapi@0.17.1 r-knitr@1.50 r-kableextra@1.4.0 r-haven@2.5.5
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://nickch-k.github.io/vtable/
Licenses: Expat
Build system: r
Synopsis: Variable Table for Variable Documentation
Description:

Automatically generates HTML variable documentation including variable names, labels, classes, value labels (if applicable), value ranges, and summary statistics. See the vignette "vtable" for a package overview.

r-venneuler 1.1-4
Propagated dependencies: r-rjava@1.0-11
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://www.rforge.net/venneuler/
Licenses: FSDG-compatible
Build system: r
Synopsis: Venn and Euler Diagrams
Description:

Calculates and displays Venn and Euler Diagrams.

r-vagam 1.1
Propagated dependencies: r-truncnorm@1.0-9 r-mvtnorm@1.3-3 r-mgcv@1.9-4 r-matrix@1.7-4 r-gamm4@0.2-7
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://cran.r-project.org/package=vagam
Licenses: GPL 3
Build system: r
Synopsis: Variational Approximations for Generalized Additive Models
Description:

Fits generalized additive models (GAMs) using a variational approximations (VA) framework. In brief, the VA framework provides a fully or at least closed to fully tractable lower bound approximation to the marginal likelihood of a GAM when it is parameterized as a mixed model (using penalized splines, say). In doing so, the VA framework aims offers both the stability and natural inference tools available in the mixed model approach to GAMs, while achieving computation times comparable to that of using the penalized likelihood approach to GAMs. See Hui et al. (2018) <doi:10.1080/01621459.2018.1518235>.

r-verbalisr 0.7.2
Propagated dependencies: r-ribd@1.7.1 r-pedtools@2.10.0
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/magnusdv/verbalisr
Licenses: GPL 3
Build system: r
Synopsis: Describe Pedigree Relationships in Words
Description:

Describe in words the genealogical relationship between two members of a given pedigree, using the algorithm in Vigeland (2022) <doi:10.1186/s12859-022-04759-y>. verbalisr is part of the pedsuite collection of packages for pedigree analysis. For a demonstration of verbalisr', see the online app QuickPed at <https://magnusdv.shinyapps.io/quickped>.

r-vvsculptor 0.4.10
Propagated dependencies: 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=vvsculptor
Licenses: Expat
Build system: r
Synopsis: Apply Manipulations to Data Frames
Description:

This package provides a set of functions for manipulating data frames in accordance with specific business rules. In addition, it includes wrapper functions for commonly used functions from the popular tidyverse package, making it easy to integrate these functions into data analysis workflows. The package is designed to streamline data preprocessing and help users quickly and efficiently perform data transformations that are specific to their business needs.

r-vmr 0.0.6
Propagated dependencies: r-jsonlite@2.0.0 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://gitlab.com/rstuff/vmr
Licenses: GPL 3+
Build system: r
Synopsis: Virtual Machines for R
Description:

Manage, provision and use Virtual Machines pre-configured for R. Develop, test and build package in a clean environment. Vagrant tool and a provider (such as Virtualbox') have to be installed.

r-vmsae 0.1.2
Propagated dependencies: r-tidyr@1.3.1 r-sf@1.0-23 r-rlang@1.1.6 r-reticulate@1.44.1 r-gridextra@2.3 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/zhenhua-wang/vmsae
Licenses: Expat
Build system: r
Synopsis: Variational Multivariate Spatial Small Area Estimation
Description:

Variational Autoencoded Multivariate Spatial Fay-Herriot models are designed to efficiently estimate population parameters in small area estimation. This package implements the variational generalized multivariate spatial Fay-Herriot model (VGMSFH) using NumPyro and PyTorch backends, as demonstrated by Wang, Parker, and Holan (2025) <doi:10.48550/arXiv.2503.14710>. The vmsae package provides utility functions to load weights of the pretrained variational autoencoders (VAEs) as well as tools to train custom VAEs tailored to users specific applications.

r-vsurf 1.2.1
Propagated dependencies: r-rpart@4.1.24 r-randomforest@4.7-1.2 r-foreach@1.5.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/robingenuer/VSURF
Licenses: GPL 2+
Build system: r
Synopsis: Variable Selection Using Random Forests
Description:

Three steps variable selection procedure based on random forests. Initially developed to handle high dimensional data (for which number of variables largely exceeds number of observations), the package is very versatile and can treat most dimensions of data, for regression and supervised classification problems. First step is dedicated to eliminate irrelevant variables from the dataset. Second step aims to select all variables related to the response for interpretation purpose. Third step refines the selection by eliminating redundancy in the set of variables selected by the second step, for prediction purpose. Genuer, R. Poggi, J.-M. and Tuleau-Malot, C. (2015) <https://journal.r-project.org/articles/RJ-2015-018/>.

r-vecctmvn 1.3.2
Propagated dependencies: r-truncnorm@1.0-9 r-truncatednormal@2.3 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-nleqslv@3.3.5 r-matrix@1.7-4 r-gpvecchia@0.1.8 r-gpgp@1.0.0
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: https://github.com/JCatwood/VeccTMVN
Licenses: GPL 2+
Build system: r
Synopsis: Multivariate Normal Probabilities using Vecchia Approximation
Description:

Under a different representation of the multivariate normal (MVN) probability, we can use the Vecchia approximation to sample the integrand at a linear complexity with respect to n. Additionally, both the SOV algorithm from Genz (92) and the exponential-tilting method from Botev (2017) can be adapted to linear complexity. The reference for the method implemented in this package is Jian Cao and Matthias Katzfuss (2024) "Linear-Cost Vecchia Approximation of Multivariate Normal Probabilities" <doi:10.48550/arXiv.2311.09426>. Two major references for the development of our method are Alan Genz (1992) "Numerical Computation of Multivariate Normal Probabilities" <doi:10.1080/10618600.1992.10477010> and Z. I. Botev (2017) "The Normal Law Under Linear Restrictions: Simulation and Estimation via Minimax Tilting" <doi:10.48550/arXiv.1603.04166>.

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