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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-svrep 0.9.1
Propagated dependencies: r-survey@4.4-8 r-sampling@2.11 r-rlang@1.1.6 r-mvtnorm@1.3-3 r-matrix@1.7-4 r-dbi@1.2.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://bschneidr.github.io/svrep/
Licenses: GPL 3+
Build system: r
Synopsis: Tools for Creating, Updating, and Analyzing Survey Replicate Weights
Description:

This package provides tools for creating and working with survey replicate weights, extending functionality of the survey package from Lumley (2004) <doi:10.18637/jss.v009.i08>. Implements bootstrap methods for complex surveys, including the generalized survey bootstrap as described by Beaumont and Patak (2012) <doi:10.1111/j.1751-5823.2011.00166.x>. Methods are provided for applying nonresponse adjustments to both full-sample and replicate weights as described by Rust and Rao (1996) <doi:10.1177/096228029600500305>. Implements methods for sample-based calibration described by Opsomer and Erciulescu (2021) <https://www150.statcan.gc.ca/n1/pub/12-001-x/2021002/article/00006-eng.htm>. Diagnostic functions are included to compare weights and weighted estimates from different sets of replicate weights.

r-svd 0.5.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/asl/svd
Licenses: Modified BSD
Build system: r
Synopsis: Interfaces to Various State-of-Art SVD and Eigensolvers
Description:

R bindings to SVD and eigensolvers (PROPACK, nuTRLan).

r-surveyexplorer 0.2.0
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-stringr@1.6.0 r-scales@1.4.0 r-rlang@1.1.6 r-purrr@1.2.0 r-gt@1.3.0 r-ggupset@0.4.1 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://cran.r-project.org/package=surveyexplorer
Licenses: Expat
Build system: r
Synopsis: Quickly Explore Complex Survey Data
Description:

Visualize and tabulate single-choice, multiple-choice, matrix-style questions from survey data. Includes ability to group cross-tabulations, frequency distributions, and plots by categorical variables and to integrate survey weights. Ideal for quickly uncovering descriptive patterns in survey data.

r-stickyr 0.1.2
Propagated dependencies: r-vctrs@0.6.5 r-tidyselect@1.2.1 r-tibble@3.3.0 r-rlang@1.1.6 r-purrr@1.2.0 r-pillar@1.11.1 r-generics@0.1.4 r-ellipsis@0.3.2 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/UchidaMizuki/stickyr
Licenses: Expat
Build system: r
Synopsis: Data Frames with Persistent Columns and Attributes
Description:

This package provides data frames that hold certain columns and attributes persistently for data processing in dplyr'.

r-ssifs 1.0.5
Propagated dependencies: r-rdpack@2.6.4 r-r2jags@0.8-9 r-plyr@1.8.9 r-netmeta@3.3-1 r-meta@8.2-1 r-igraph@2.2.1 r-gtools@3.9.5 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/georgiosseitidis/ssifs
Licenses: GPL 3+
Build system: r
Synopsis: Stochastic Search Inconsistency Factor Selection
Description:

Evaluating the consistency assumption of Network Meta-Analysis both globally and locally in the Bayesian framework. Inconsistencies are located by applying Bayesian variable selection to the inconsistency factors. The implementation of the method is described by Seitidis et al. (2023) <doi:10.1002/sim.9891>.

r-semmcci 1.1.5
Propagated dependencies: r-mice@3.18.0 r-lavaan@0.6-20
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/jeksterslab/semmcci
Licenses: Expat
Build system: r
Synopsis: Monte Carlo Confidence Intervals in Structural Equation Modeling
Description:

Monte Carlo confidence intervals for free and defined parameters in models fitted in the structural equation modeling package lavaan can be generated using the semmcci package. semmcci has three main functions, namely, MC(), MCMI(), and MCStd(). The output of lavaan is passed as the first argument to the MC() function or the MCMI() function to generate Monte Carlo confidence intervals. Monte Carlo confidence intervals for the standardized estimates can also be generated by passing the output of the MC() function or the MCMI() function to the MCStd() function. A description of the package and code examples are presented in Pesigan and Cheung (2024) <doi:10.3758/s13428-023-02114-4>.

r-stat2 0.1.0
Propagated dependencies: r-shiny@1.11.1 r-rpivottable@0.3.0 r-rmarkdown@2.30 r-psycho@0.6.1 r-psych@2.5.6 r-hmisc@5.2-4 r-dplyr@1.1.4 r-corrgram@1.14
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=STAT2
Licenses: GPL 2
Build system: r
Synopsis: Interactive Document for Working with Basic Statistical Analysis
Description:

An interactive document on the topic of basic statistical analysis using rmarkdown and shiny packages. Runtime examples are provided in the package function as well as at <https://jarvisatharva.shinyapps.io/StatisticsPrimer/>.

r-svtools 0.9-5
Propagated dependencies: r-svmisc@1.4.3 r-codetools@0.2-20
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: http://www.sciviews.org/SciViews-R
Licenses: GPL 2
Build system: r
Synopsis: Wrappers for Tools in Other Packages for IDE Friendliness
Description:

Set of tools aimed at wrapping some of the functionalities of the packages tools, utils and codetools into a nicer format so that an IDE can use them.

r-stoichutilities 1.0.2
Propagated dependencies: r-units@1.0-0 r-tidyr@1.3.1 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-purrr@1.2.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-jsonlite@2.0.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/STOICH-project/STOICH-utilities
Licenses: GPL 3+
Build system: r
Synopsis: User Tools for Accessing the STOICH Project Database
Description:

User tools for working with The STOICH (Stoichiometric Traits of Organisms in their Chemical Habitats) Project database <https://snr-stoich.unl.edu/>. This package is designed to aid in data discovery, filtering, pairing water samples with organism samples, and merging data tables to assist users in preparing data for analyses. For additional examples see "Additional Examples" and the readme file at <https://github.com/STOICH-project/STOICH-utilities>.

r-simputation 0.2.9
Propagated dependencies: r-vim@6.2.6 r-rpart@4.1.24 r-randomforest@4.7-1.2 r-norm@1.0-11.1 r-missforest@1.6.1 r-mass@7.3-65 r-gower@1.0.2 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/markvanderloo/simputation
Licenses: GPL 3
Build system: r
Synopsis: Simple Imputation
Description:

Easy to use interfaces to a number of imputation methods that fit in the not-a-pipe operator of the magrittr package.

r-smtl 0.1.0
Propagated dependencies: r-juliaconnector@1.1.5 r-juliacall@0.17.6 r-glmnet@4.1-10 r-dplyr@1.1.4 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/gloewing/sMTL
Licenses: Expat
Build system: r
Synopsis: Sparse Multi-Task Learning
Description:

This package implements L0-constrained Multi-Task Learning and domain generalization algorithms. The algorithms are coded in Julia allowing for fast implementations of the coordinate descent and local combinatorial search algorithms. For more details, see a preprint of the paper: Loewinger et al., (2022) <arXiv:2212.08697>.

r-spatgeom 0.3.0
Propagated dependencies: r-sf@1.0-23 r-scales@1.4.0 r-purrr@1.2.0 r-lwgeom@0.2-14 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-cowplot@1.2.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/maikol-solis/spatgeom
Licenses: Expat
Build system: r
Synopsis: Geometric Spatial Point Analysis
Description:

The implementation to perform the geometric spatial point analysis developed in Hernández & Solàs (2022) <doi:10.1007/s00180-022-01244-1>. It estimates the geometric goodness-of-fit index for a set of variables against a response one based on the sf package. The package has methods to print and plot the results.

r-sparselink 1.0.0
Propagated dependencies: r-xrnet@1.0.1 r-spls@2.3-2 r-proc@1.19.0.1 r-mvtnorm@1.3-3 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/rauschenberger/sparselink
Licenses: Expat
Build system: r
Synopsis: Sparse Regression for Related Problems
Description:

Estimates sparse regression models (i.e., with few non-zero coefficients) in high-dimensional multi-task learning and transfer learning settings, as proposed by Rauschenberger et al. (2025) <https://orbilu.uni.lu/handle/10993/63425>.

r-strs 0.1.0
Propagated dependencies: r-stringi@1.8.7
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/pythonicr/strs
Licenses: Expat
Build system: r
Synopsis: 'Python' Style String Functions
Description:

This package provides a comprehensive set of string manipulation functions based on those found in Python without relying on reticulate'. It provides functions that intend to (1) make it easier for users familiar with Python to work with strings, (2) reduce the complexity often associated with string operations, (3) and enable users to write more readable and maintainable code that manipulates strings.

r-syscselection 1.0.2
Propagated dependencies: r-pracma@2.4.6
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SyScSelection
Licenses: CC0
Build system: r
Synopsis: Systematic Scenario Selection for Stress Testing
Description:

Quasi-Monte-Carlo algorithm for systematic generation of shock scenarios from an arbitrary multivariate elliptical distribution. The algorithm selects a systematic mesh of arbitrary fineness that approximately evenly covers an isoprobability ellipsoid in d dimensions (Flood, Mark D. & Korenko, George G. (2013) <doi:10.1080/14697688.2014.926018>). This package is the R analogy to the Matlab code published by Flood & Korenko in above-mentioned paper.

r-shapper 0.1.3
Propagated dependencies: r-reticulate@1.44.1 r-ggplot2@4.0.1 r-dalex@2.5.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/ModelOriented/shapper
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Wrapper of Python Library 'shap'
Description:

This package provides SHAP explanations of machine learning models. In applied machine learning, there is a strong belief that we need to strike a balance between interpretability and accuracy. However, in field of the Interpretable Machine Learning, there are more and more new ideas for explaining black-box models. One of the best known method for local explanations is SHapley Additive exPlanations (SHAP) introduced by Lundberg, S., et al., (2016) <arXiv:1705.07874> The SHAP method is used to calculate influences of variables on the particular observation. This method is based on Shapley values, a technique used in game theory. The R package shapper is a port of the Python library shap'.

r-socialranking 1.2.0
Propagated dependencies: r-rlang@1.1.6 r-relations@0.6-15 r-rdpack@2.6.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/jassler/socialranking
Licenses: GPL 3
Build system: r
Synopsis: Social Ranking Solutions for Power Relations on Coalitions
Description:

The notion of power index has been widely used in literature to evaluate the influence of individual players (e.g., voters, political parties, nations, stockholders, etc.) involved in a collective decision situation like an electoral system, a parliament, a council, a management board, etc., where players may form coalitions. Traditionally this ranking is determined through numerical evaluation. More often than not however only ordinal data between coalitions is known. The package socialranking offers a set of solutions to rank players based on a transitive ranking between coalitions, including through CP-Majority, ordinal Banzhaf or lexicographic excellence solution summarized by Tahar Allouche, Bruno Escoffier, Stefano Moretti and Meltem à ztürk (2020, <doi:10.24963/ijcai.2020/3>).

r-sparsepp 1.22
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/greg7mdp/sparsepp
Licenses: Modified BSD
Build system: r
Synopsis: 'Rcpp' Interface to 'sparsepp'
Description:

This package provides interface to sparsepp - fast, memory efficient hash map. It is derived from Google's excellent sparsehash implementation. We believe sparsepp provides an unparalleled combination of performance and memory usage, and will outperform your compiler's unordered_map on both counts. Only Google's dense_hash_map is consistently faster, at the cost of much greater memory usage (especially when the final size of the map is not known in advance).

r-slimrec 0.1.0
Propagated dependencies: r-pbapply@1.7-4 r-matrix@1.7-4 r-glmnet@4.1-10 r-bigmemory@4.6.4 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=slimrec
Licenses: GPL 3
Build system: r
Synopsis: Sparse Linear Method to Predict Ratings and Top-N Recommendations
Description:

Sparse Linear Method(SLIM) predicts ratings and top-n recommendations suited for sparse implicit positive feedback systems. SLIM is decomposed into multiple elasticnet optimization problems which are solved in parallel over multiple cores. The package is based on "SLIM: Sparse Linear Methods for Top-N Recommender Systems" by Xia Ning and George Karypis <doi:10.1109/ICDM.2011.134>.

r-sparsemvn 0.2.2
Propagated dependencies: r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://braunm.github.io/sparseMVN/
Licenses: FSDG-compatible
Build system: r
Synopsis: Multivariate Normal Functions for Sparse Covariance and Precision Matrices
Description:

Computes multivariate normal (MVN) densities, and samples from MVN distributions, when the covariance or precision matrix is sparse.

r-samplrdata 1.0.0
Propagated dependencies: r-rdpack@2.6.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/lucas-castillo/samplrData
Licenses: FSDG-compatible
Build system: r
Synopsis: Datasets from the SAMPLING Project
Description:

This package contains human behaviour datasets collected by the SAMPLING project (<https://sampling.warwick.ac.uk>).

r-stmgui 0.1.6
Propagated dependencies: r-tm@0.7-16 r-stm@1.3.8 r-shinythemes@1.2.0 r-shinyjs@2.1.0 r-shinybs@0.61.1 r-shiny@1.11.1 r-markdown@2.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=stmgui
Licenses: Expat
Build system: r
Synopsis: Shiny Application for Creating STM Models
Description:

This package provides an application that acts as a GUI for the stm text analysis package.

r-ssmousetrack 1.1.7
Propagated dependencies: r-stanheaders@2.32.10 r-rstantools@2.5.0 r-rstan@2.32.7 r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-ggplot2@4.0.1 r-dtw@1.23-1 r-cowplot@1.2.0 r-circstats@0.2-7 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=ssMousetrack
Licenses: GPL 3+
Build system: r
Synopsis: Bayesian State-Space Modeling of Mouse-Tracking Experiments via Stan
Description:

Estimates previously compiled state-space modeling for mouse-tracking experiments using the rstan package, which provides the R interface to the Stan C++ library for Bayesian estimation.

r-shp2graph 1-0
Propagated dependencies: r-sp@2.2-0 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=shp2graph
Licenses: GPL 2+
Build system: r
Synopsis: Convert a 'SpatialLinesDataFrame' -Class Object to an 'igraph'-Class Object
Description:

This package provides functions for converting and processing network data from a SpatialLinesDataFrame -Class object to an igraph'-Class object.

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