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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-stfit 0.99.9
Propagated dependencies: r-rcpp@1.1.0 r-rcolorbrewer@1.1-3 r-rastervis@0.51.7 r-raster@3.6-32 r-matrix@1.7-4 r-foreach@1.5.2 r-fda@6.3.0 r-doparallel@1.0.17 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=stfit
Licenses: GPL 3
Build system: r
Synopsis: Spatio-Temporal Functional Imputation Tool
Description:

This package provides a general spatiotemporal satellite image imputation method based on sparse functional data analytic techniques. The imputation method applies and extends the Functional Principal Analysis by Conditional Estimation (PACE). The underlying idea for the proposed procedure is to impute a missing pixel by borrowing information from temporally and spatially contiguous pixels based on the best linear unbiased prediction.

r-scgwr 0.1.2-21
Propagated dependencies: r-spdata@2.3.4 r-sp@2.2-0 r-optimparallel@1.0-2 r-fnn@1.1.4.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=scgwr
Licenses: GPL 2+
Build system: r
Synopsis: Scalable Geographically Weighted Regression
Description:

Fast and regularized version of GWR for large dataset, detailed in Murakami, Tsutsumida, Yoshida, Nakaya, and Lu (2019) <arXiv:1905.00266>.

r-simdag 0.5.0
Propagated dependencies: r-rlang@1.1.6 r-rfast@2.1.5.2 r-igraph@2.2.1 r-ggdag@0.2.13 r-data-table@1.17.8 r-dagitty@0.3-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/RobinDenz1/simDAG
Licenses: GPL 3+
Build system: r
Synopsis: Simulate Data from a (Time-Dependent) Causal DAG
Description:

Simulate complex data from a given directed acyclic graph and information about each individual node. Root nodes are simply sampled from the specified distribution. Child Nodes are simulated according to one of many implemented regressions, such as logistic regression, linear regression, poisson regression or any other function. Also includes a comprehensive framework for discrete-time simulation, discrete-event simulation, and networks-based simulation which can generate even more complex longitudinal and dependent data. For more details, see Robin Denz, Nina Timmesfeld (2025) <doi:10.48550/arXiv.2506.01498>.

r-shadowvimp 1.0.2
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-rlang@1.1.6 r-ranger@0.17.0 r-patchwork@1.3.2 r-magrittr@2.0.4 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-ggforce@0.5.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/OktawiaStaburo/shadowVIMP
Licenses: FSDG-compatible
Build system: r
Synopsis: Covariate Selection Based on VIMP Permutation-Like Testing
Description:

This package provides a statistical method for reducing the number of covariates in an analysis by evaluating Variable Importance Measures (VIMPs) derived from the Random Forest algorithm. It performs statistical tests on the VIMPs and outputs whether the covariate is significant along with the p-values.

r-spatialcovariance 0.6-9
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=spatialCovariance
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Computation of Spatial Covariance Matrices for Data on Rectangles
Description:

This package provides functions that compute the spatial covariance matrix for the matern and power classes of spatial models, for data that arise on rectangular units. This code can also be used for the change of support problem and for spatial data that arise on irregularly shaped regions like counties or zipcodes by laying a fine grid of rectangles and aggregating the integrals in a form of Riemann integration.

r-softclassval 1.1.0
Propagated dependencies: r-svunit@1.0.8 r-arrayhelpers@1.1-0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: http://softclassval.r-forge.r-project.org/
Licenses: GPL 3+
Build system: r
Synopsis: Soft Classification Performance Measures
Description:

An extension of sensitivity, specificity, positive and negative predictive value to continuous predicted and reference memberships in [0, 1].

r-semlrtp 0.1.1
Propagated dependencies: r-pbapply@1.7-4 r-lavaan@0.6-20
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://sfcheung.github.io/semlrtp/
Licenses: GPL 3+
Build system: r
Synopsis: Likelihood Ratio Test P-Values for Structural Equation Models
Description:

Computes likelihood ratio test (LRT) p-values for free parameters in a structural equation model. Currently supports models fitted by the lavaan package by Rosseel (2012) <doi:10.18637/jss.v048.i02>.

r-sdchierarchies 0.22.0
Propagated dependencies: r-shinytree@0.3.1 r-shinythemes@1.2.0 r-shinyjs@2.1.0 r-shiny@1.11.1 r-rlang@1.1.6 r-rcpp@1.1.0 r-jsonlite@2.0.0 r-data-table@1.17.8 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/bernhard-da/sdcHierarchies
Licenses: GPL 3
Build system: r
Synopsis: Create and (Interactively) Modify Nested Hierarchies
Description:

This package provides functionality to generate, (interactively) modify (by adding, removing and renaming nodes) and convert nested hierarchies between different formats. These tree like structures can be used to define for example complex hierarchical tables used for statistical disclosure control.

r-semblance 1.1.0
Propagated dependencies: r-performanceanalytics@2.0.8 r-msos@1.2.0 r-fields@17.1 r-desctools@0.99.60
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=Semblance
Licenses: GPL 2
Build system: r
Synopsis: Data-Driven Similarity Kernel on Probability Spaces
Description:

We present a rank-based Mercer kernel to compute a pair-wise similarity metric corresponding to informative representation of data. We tailor the development of a kernel to encode our prior knowledge about the data distribution over a probability space. The philosophical concept behind our construction is that objects whose feature values fall on the extreme of that featureâ s probability mass distribution are more similar to each other, than objects whose feature values lie closer to the mean. Semblance emphasizes features whose values lie far away from the mean of their probability distribution. The kernel relies on properties empirically determined from the data and does not assume an underlying distribution. The use of feature ranks on a probability space ensures that Semblance is computational efficacious, robust to outliers, and statistically stable, thus making it widely applicable algorithm for pattern analysis. The output from the kernel is a square, symmetric matrix that gives proximity values between pairs of observations.

r-synthesisr 0.3.0
Propagated dependencies: r-stringdist@0.9.15
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=synthesisr
Licenses: GPL 3
Build system: r
Synopsis: Import, Assemble, and Deduplicate Bibliographic Datasets
Description:

This package provides a critical first step in systematic literature reviews and mining of academic texts is to identify relevant texts from a range of sources, particularly databases such as Web of Science or Scopus'. These databases often export in different formats or with different metadata tags. synthesisr expands on the tools outlined by Westgate (2019) <doi:10.1002/jrsm.1374> to import bibliographic data from a range of formats (such as bibtex', ris', or ciw') in a standard way, and allows merging and deduplication of the resulting dataset.

r-slideview 0.2.1
Propagated dependencies: r-viridislite@0.4.2 r-terra@1.8-86 r-raster@3.6-32 r-lattice@0.22-7 r-htmlwidgets@1.6.4 r-htmltools@0.5.8.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://r-spatial.github.io/slideview/
Licenses: Expat
Build system: r
Synopsis: Compare Raster Images Side by Side with a Slider
Description:

Create a side-by-side view of raster(image)s with an interactive slider to switch between regions of the images. This can be especially useful for image comparison of the same region at different time stamps.

r-spanishoddata 0.2.2
Propagated dependencies: r-xml2@1.5.0 r-tibble@3.3.0 r-stringr@1.6.0 r-sf@1.0-23 r-rlang@1.1.6 r-readr@2.1.6 r-rdpack@2.6.4 r-purrr@1.2.0 r-paws-storage@0.9.0 r-parallelly@1.45.1 r-openssl@2.3.4 r-memoise@2.0.1 r-lubridate@1.9.4 r-lifecycle@1.0.4 r-jsonlite@2.0.0 r-httr2@1.2.1 r-glue@1.8.0 r-fs@1.6.6 r-duckdb@1.4.2 r-dplyr@1.1.4 r-digest@0.6.39 r-dbi@1.2.3 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://rOpenSpain.github.io/spanishoddata/
Licenses: Expat
Build system: r
Synopsis: Get Spanish Origin-Destination Data
Description:

Gain seamless access to origin-destination (OD) data from the Spanish Ministry of Transport, hosted at <https://www.transportes.gob.es/ministerio/proyectos-singulares/estudios-de-movilidad-con-big-data/opendata-movilidad>. This package simplifies the management of these large datasets by providing tools to download zone boundaries, handle associated origin-destination data, and process it efficiently with the duckdb database interface. Local caching minimizes repeated downloads, streamlining workflows for researchers and analysts. Methods described in Kotov et al. (2026) <doi:10.1177/23998083251415040>. Extensive documentation is available at <https://ropenspain.github.io/spanishoddata/index.html>, offering guides on creating static and dynamic mobility flow visualizations and transforming large datasets into analysis-ready formats.

r-sgl 1.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SGL
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Fit a GLM (or Cox Model) with a Combination of Lasso and Group Lasso Regularization
Description:

Fit a regularized generalized linear model via penalized maximum likelihood. The model is fit for a path of values of the penalty parameter. Fits linear, logistic and Cox models.

r-sdstudio 0.2.0
Propagated dependencies: r-surveydown@1.0.1 r-shinyace@0.4.4 r-shiny@1.11.1 r-rpostgres@1.4.8 r-pool@1.0.4 r-later@1.4.4 r-htmltools@0.5.8.1 r-dt@0.34.0 r-dotenv@1.0.3 r-dbi@1.2.3 r-bslib@0.9.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://sdstudio.surveydown.org
Licenses: Expat
Build system: r
Synopsis: Companion Application for the 'surveydown' Survey Platform
Description:

Companion package that supports the surveydown survey platform (<https://surveydown.org>). The default method for working with a surveydown survey is to edit the plain text survey.qmd and app.R files. With sdstudio', you can create, preview and manage surveys with a shiny application as a graphical user interface.

r-sonify 0.0-1
Propagated dependencies: r-tuner@1.4.7
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sonify
Licenses: GPL 2+
Build system: r
Synopsis: Data Sonification - Turning Data into Sound
Description:

Sonification (or audification) is the process of representing data by sounds in the audible range. This package provides the R function sonify() that transforms univariate data, sampled at regular or irregular intervals, into a continuous sound with time-varying frequency. The ups and downs in frequency represent the ups and downs in the data. Sonify provides a substitute for R's plot function to simplify data analysis for the visually impaired.

r-semantic-dashboard 0.2.1
Propagated dependencies: r-shiny-semantic@0.5.1 r-shiny@1.11.1 r-htmltools@0.5.8.1 r-glue@1.8.0 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=semantic.dashboard
Licenses: Expat
Build system: r
Synopsis: Dashboard with Fomantic UI Support for Shiny
Description:

It offers functions for creating dashboard with Fomantic UI.

r-simpleupset 0.1.4
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-scales@1.4.0 r-s7@0.2.1 r-rlang@1.1.6 r-patchwork@1.3.2 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/smped/SimpleUpset
Licenses: GPL 3
Build system: r
Synopsis: Create Upset Plots
Description:

Create Upset plots using a combination of ggplot2 and patchwork'.

r-sparrpowr 0.2.9
Propagated dependencies: r-terra@1.8-86 r-spatstat-random@3.4-3 r-spatstat-geom@3.6-1 r-sparr@2.3-16 r-lifecycle@1.0.4 r-iterators@1.0.14 r-future@1.68.0 r-foreach@1.5.2 r-fields@17.1 r-dorng@1.8.6.2 r-dofuture@1.1.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/machiela-lab/sparrpowR
Licenses: ASL 2.0
Build system: r
Synopsis: Power Analysis to Detect Spatial Relative Risk Clusters
Description:

Calculate the statistical power to detect clusters using kernel-based spatial relative risk functions that are estimated using the sparr package. Details about the sparr package methods can be found in the tutorial: Davies et al. (2018) <doi:10.1002/sim.7577>. Details about kernel density estimation can be found in J. F. Bithell (1990) <doi:10.1002/sim.4780090616>. More information about relative risk functions using kernel density estimation can be found in J. F. Bithell (1991) <doi:10.1002/sim.4780101112>.

r-spetestnp 1.1.0
Propagated dependencies: r-foreach@1.5.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/HippolyteBoucher/SpeTestNP
Licenses: GPL 2
Build system: r
Synopsis: Non-Parametric Tests of Parametric Specifications
Description:

This package performs non-parametric tests of parametric specifications. Five tests are available. Specific bandwidth and kernel methods can be chosen along with many other options. Allows parallel computing to quickly compute p-values based on the bootstrap. Methods implemented in the package are H.J. Bierens (1982) <doi:10.1016/0304-4076(82)90105-1>, J.C. Escanciano (2006) <doi:10.1017/S0266466606060506>, P.L. Gozalo (1997) <doi:10.1016/S0304-4076(97)86571-2>, P. Lavergne and V. Patilea (2008) <doi:10.1016/j.jeconom.2007.08.014>, P. Lavergne and V. Patilea (2012) <doi:10.1198/jbes.2011.07152>, J.H. Stock and M.W. Watson (2006) <doi:10.1111/j.1538-4616.2007.00014.x>, C.F.J. Wu (1986) <doi:10.1214/aos/1176350142>, J. Yin, Z. Geng, R. Li, H. Wang (2010) <https://www.jstor.org/stable/24309002> and J.X. Zheng (1996) <doi:10.1016/0304-4076(95)01760-7>.

r-sensominer 1.28
Propagated dependencies: r-reshape2@1.4.5 r-kernsmooth@2.23-26 r-gtools@3.9.5 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-factominer@2.12 r-cluster@2.1.8.1 r-algdesign@1.2.1.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: http://sensominer.free.fr
Licenses: GPL 2+
Build system: r
Synopsis: Sensory Data Analysis
Description:

Statistical Methods to Analyse Sensory Data. SensoMineR: A package for sensory data analysis. S. Le and F. Husson (2008).

r-scina 1.2.0
Propagated dependencies: r-mass@7.3-65 r-gplots@3.2.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SCINA
Licenses: GPL 2
Build system: r
Synopsis: Semi-Supervised Category Identification and Assignment Tool
Description:

An automatic cell type detection and assignment algorithm for single cell RNA-Seq and Cytof/FACS data. SCINA is capable of assigning cell type identities to a pool of cells profiled by scRNA-Seq or Cytof/FACS data with prior knowledge of markers, such as genes and protein symbols that are highly or lowly expressed in each category. See Zhang Z, et al (2019) <doi:10.3390/genes10070531> for more details.

r-simstudy 0.9.2
Propagated dependencies: r-rcpp@1.1.0 r-pbv@0.5-47 r-mvnfast@0.2.8 r-glue@1.8.0 r-fastglm@0.0.3 r-data-table@1.17.8 r-backports@1.5.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/kgoldfeld/simstudy
Licenses: GPL 3
Build system: r
Synopsis: Simulation of Study Data
Description:

Simulates data sets in order to explore modeling techniques or better understand data generating processes. The user specifies a set of relationships between covariates, and generates data based on these specifications. The final data sets can represent data from randomized control trials, repeated measure (longitudinal) designs, and cluster randomized trials. Missingness can be generated using various mechanisms (MCAR, MAR, NMAR).

r-statnetweb 0.6.1
Propagated dependencies: r-sna@2.8 r-shiny@1.11.1 r-rcolorbrewer@1.1-3 r-network@1.19.0 r-latticeextra@0.6-31 r-lattice@0.22-7 r-ergm@4.12.0 r-dt@0.34.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://statnet.org
Licenses: GPL 3
Build system: r
Synopsis: Shiny App for Network Modeling with 'statnet'
Description:

This package provides a graphical user interface for cross-sectional network modeling with the statnet software suite <https://github.com/statnet>.

r-salso 0.3.57
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/dbdahl/salso
Licenses: Expat ASL 2.0
Build system: r
Synopsis: Search Algorithms and Loss Functions for Bayesian Clustering
Description:

The SALSO algorithm is an efficient randomized greedy search method to find a point estimate for a random partition based on a loss function and posterior Monte Carlo samples. The algorithm is implemented for many loss functions, including the Binder loss and a generalization of the variation of information loss, both of which allow for unequal weights on the two types of clustering mistakes. Efficient implementations are also provided for Monte Carlo estimation of the posterior expected loss of a given clustering estimate. See Dahl, Johnson, Müller (2022) <doi:10.1080/10618600.2022.2069779>.

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