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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-secutrialr 1.3.3
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-readxl@1.4.5 r-readr@2.1.6 r-purrr@1.2.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-haven@2.5.5 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/SwissClinicalTrialOrganisation/secuTrialR
Licenses: Expat
Build system: r
Synopsis: Handling of Data from the Clinical Data Management System 'secuTrial'
Description:

Seamless and standardized interaction with data exported from the clinical data management system (CDMS) secuTrial'<https://www.secutrial.com>. The primary data export the package works with is a standard non-rectangular export.

r-synmicrodata 2.1.3
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=synMicrodata
Licenses: GPL 3+
Build system: r
Synopsis: Synthetic Microdata Generator
Description:

This tool fits a non-parametric Bayesian model called a "hierarchically coupled mixture model with local dependence (HCMM-LD)" to the original microdata in order to generate synthetic microdata for privacy protection. The non-parametric feature of the adopted model is useful for capturing the joint distribution of the original input data in a highly flexible manner, leading to the generation of synthetic data whose distributional features are similar to that of the input data. The package allows the original input data to have missing values and impute them with the posterior predictive distribution, so no missing values exist in the synthetic data output. The method builds on the work of Murray and Reiter (2016) <doi:10.1080/01621459.2016.1174132>.

r-spex 0.7.1
Propagated dependencies: r-sp@2.2-0 r-reproj@0.7.0 r-raster@3.6-32 r-quadmesh@0.5.5 r-crsmeta@0.3.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://mdsumner.github.io/spex/
Licenses: GPL 3
Build system: r
Synopsis: Spatial Extent Tools
Description:

This package provides functions to produce a fully fledged geo-spatial object extent as a SpatialPolygonsDataFrame'. Also included are functions to generate polygons from raster data using quadmesh techniques, a round number buffered extent, and general spatial-extent and raster-like extent helpers missing from the originating packages. Some latitude-based tools for polar maps are included.

r-sensitivitycalibration 0.0.1
Propagated dependencies: r-stringi@1.8.7 r-splitstackshape@1.4.8 r-relaimpo@2.2-7 r-plotly@4.11.0 r-ggrepel@0.9.6 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sensitivityCalibration
Licenses: Expat
Build system: r
Synopsis: Calibrated Sensitivity Analysis for Matched Observational Studies
Description:

This package implements the calibrated sensitivity analysis approach for matched observational studies. Our sensitivity analysis framework views matched sets as drawn from a super-population. The unmeasured confounder is modeled as a random variable. We combine matching and model-based covariate-adjustment methods to estimate the treatment effect. The hypothesized unmeasured confounder enters the picture as a missing covariate. We adopt a state-of-art Expectation Maximization (EM) algorithm to handle this missing covariate problem in generalized linear models (GLMs). As our method also estimates the effect of each observed covariate on the outcome and treatment assignment, we are able to calibrate the unmeasured confounder to observed covariates. Zhang, B., Small, D. S. (2018). <arXiv:1812.00215>.

r-scspatialsim 0.1.4
Propagated dependencies: r-tidyr@1.3.1 r-spatstat-random@3.4-3 r-spatstat-geom@3.6-1 r-proxy@0.4-27 r-pbmcapply@1.5.1 r-magrittr@2.0.4 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-crayon@1.5.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/FridleyLab/scSpatialSIM
Licenses: Expat
Build system: r
Synopsis: Point Pattern Simulator for Spatial Cellular Data
Description:

Single cell resolution data has been valuable in learning about tissue microenvironments and interactions between cells or spots. This package allows for the simulation of this level of data, be it single cell or â spotsâ , in both a univariate (single metric or cell type) and bivariate (2 or more metrics or cell types) ways. As more technologies come to marker, more methods will be developed to derive spatial metrics from the data which will require a way to benchmark methods against each other. Additionally, as the field currently stands, there is not a gold standard method to be compared against. We set out to develop an R package that will allow users to simulate point patterns that can be biologically informed from different tissue domains, holes, and varying degrees of clustering/colocalization. The data can be exported as spatial files and a summary file (like HALO'). <https://github.com/FridleyLab/scSpatialSIM/>.

r-systemicr 0.1.0
Propagated dependencies: r-xts@0.14.1 r-quantreg@6.1 r-matrix@1.7-4 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=SystemicR
Licenses: GPL 3
Build system: r
Synopsis: Monitoring Systemic Risk
Description:

The past decade has demonstrated an increased need to better understand risks leading to systemic crises. This framework offers scholars, practitioners and policymakers a useful toolbox to explore such risks in financial systems. Specifically, this framework provides popular econometric and network measures to monitor systemic risk and to measure the consequences of regulatory decisions. These systemic risk measures are based on the frameworks of Adrian and Brunnermeier (2016) <doi:10.1257/aer.20120555> and Billio, Getmansky, Lo and Pelizzon (2012) <doi:10.1016/j.jfineco.2011.12.010>.

r-secretsprovider 1.0.1
Propagated dependencies: r-getpass@0.2-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://CRAN.R-project.org/package=SecretsProvider
Licenses: ASL 2.0
Build system: r
Synopsis: Save and Retrieve Name-Value Pairs to and from a File
Description:

Facilitates secret management by storing credentials in a dedicated file, keeping them out of your code base. The secrets are stored without encryption. This package is compatible with secrets stored by the SecretsProvider Python package <https://pypi.org/project/SecretsProvider/>.

r-ssmsn 0.2.0
Propagated dependencies: r-mcmcpack@1.7-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=ssmsn
Licenses: GPL 2+
Build system: r
Synopsis: Scale-Shape Mixtures of Skew-Normal Distributions
Description:

It provides the density and random number generator for the Scale-Shape Mixtures of Skew-Normal Distributions proposed by Jamalizadeh and Lin (2016) <doi:10.1007/s00180-016-0691-1>.

r-sparklyr-flint 0.2.2
Propagated dependencies: r-sparklyr@1.9.3 r-rlang@1.1.6 r-dplyr@1.1.4 r-dbplyr@2.5.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: <https://github.com/r-spark/sparklyr.flint>
Licenses: ASL 2.0
Build system: r
Synopsis: Sparklyr Extension for 'Flint'
Description:

This sparklyr extension makes Flint time series library functionalities (<https://github.com/twosigma/flint>) easily accessible through R.

r-sazedr 2.0.2
Propagated dependencies: r-zoo@1.8-14 r-pracma@2.4.6 r-fftwtools@0.9-11 r-dplyr@1.1.4 r-bspec@1.6
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/mtoller/autocorr_season_length_detection/
Licenses: GPL 2
Build system: r
Synopsis: Parameter-Free Domain-Agnostic Season Length Detection in Time Series
Description:

Spectral and Average Autocorrelation Zero Distance Density ('sazed') is a method for estimating the season length of a seasonal time series. sazed is aimed at practitioners, as it employs only domain-agnostic preprocessing and does not depend on parameter tuning or empirical constants. The computation of sazed relies on the efficient autocorrelation computation methods suggested by Thibauld Nion (2012, URL: <https://etudes.tibonihoo.net/literate_musing/autocorrelations.html>) and by Bob Carpenter (2012, URL: <https://lingpipe-blog.com/2012/06/08/autocorrelation-fft-kiss-eigen/>).

r-shinyanimate 0.4.0
Propagated dependencies: r-shiny@1.11.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/Swechhya/shinyanimate
Licenses: Expat
Build system: r
Synopsis: Animation for 'shiny' Elements
Description:

An extension of animate.css that allows user to easily add animations to any UI element in shiny app using the elements id.

r-sqrl 1.0.2
Propagated dependencies: r-rodbc@1.3-26.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SQRL
Licenses: GPL 3
Build system: r
Synopsis: Enhances Interaction with 'ODBC' Databases
Description:

This package provides simple and powerful interfaces that facilitate interaction with ODBC data sources. Each data source gets its own unique and dedicated interface, wrapped around RODBC'. Communication settings are remembered between queries, and are managed silently in the background. The interfaces support multi-statement SQL scripts, which can be parameterised via metaprogramming structures and embedded R expressions.

r-segmgarch 1.3
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mvtnorm@1.3-3 r-iterators@1.0.14 r-foreach@1.5.2 r-fgarch@4052.93 r-doparallel@1.0.17 r-corpcor@1.6.10
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=segMGarch
Licenses: GPL 2+
Build system: r
Synopsis: Multiple Change-Point Detection for High-Dimensional GARCH Processes
Description:

This package implements a segmentation algorithm for multiple change-point detection in high-dimensional GARCH processes. It simultaneously segments GARCH processes by identifying common change-points, each of which can be shared by a subset or all of the component time series as a change-point in their within-series and/or cross-sectional correlation structure.

r-sperich 1.5-9
Propagated dependencies: r-sp@2.2-0 r-raster@3.6-32 r-foreach@1.5.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sperich
Licenses: GPL 2+
Build system: r
Synopsis: Auxiliary Functions to Estimate Centers of Biodiversity
Description:

This package provides some easy-to-use functions to interpolate species range based on species occurrences and to estimate centers of biodiversity.

r-smer 0.0.2
Propagated dependencies: r-tidyr@1.3.1 r-testthat@3.3.0 r-rhdf5lib@1.32.0 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-mvmapit@2.0.4 r-logging@0.10-108 r-highfive@3.3.0 r-genio@1.1.2 r-dplyr@1.1.4 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/lcrawlab/sme
Licenses: Expat
Build system: r
Synopsis: Sparse Marginal Epistasis Test
Description:

The Sparse Marginal Epistasis Test is a computationally efficient genetics method which detects statistical epistasis in complex traits; see Stamp et al. (2025, <doi:10.1101/2025.01.11.632557>) for details.

r-simsem 0.5-17
Propagated dependencies: r-lavaan@0.6-20
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://simsem.org/
Licenses: GPL 2+
Build system: r
Synopsis: SIMulated Structural Equation Modeling
Description:

This package provides an easy framework for Monte Carlo simulation in structural equation modeling, which can be used for various purposes, such as such as model fit evaluation, power analysis, or missing data handling and planning.

r-str 0.7.1
Propagated dependencies: r-sparsem@1.84-2 r-quantreg@6.1 r-matrix@1.7-4 r-forecast@8.24.0 r-foreach@1.5.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://pkg.robjhyndman.com/stR/
Licenses: GPL 3
Build system: r
Synopsis: Seasonal Trend Decomposition Using Regression
Description:

This package provides methods for decomposing seasonal data: STR (a Seasonal-Trend time series decomposition procedure based on Regression) and Robust STR. In some ways, STR is similar to Ridge Regression and Robust STR can be related to LASSO. They allow for multiple seasonal components, multiple linear covariates with constant, flexible and seasonal influence. Seasonal patterns (for both seasonal components and seasonal covariates) can be fractional and flexible over time; moreover they can be either strictly periodic or have a more complex topology. The methods provide confidence intervals for the estimated components. The methods can also be used for forecasting.

r-shinywgd 1.0.0
Dependencies: pandoc@2.19.2 pandoc@2.19.2
Propagated dependencies: r-vroom@1.6.6 r-tidyr@1.3.1 r-stringr@1.6.0 r-shinyalert@3.1.0 r-shiny@1.11.1 r-seqinr@4.2-36 r-mclust@6.1.2 r-ks@1.15.1 r-jsonlite@2.0.0 r-httr@1.4.7 r-htmltools@0.5.8.1 r-fs@1.6.6 r-dplyr@1.1.4 r-data-table@1.17.8 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=shinyWGD
Licenses: GPL 3
Build system: r
Synopsis: 'Shiny' Application for Whole Genome Duplication Analysis
Description:

This package provides a comprehensive Shiny application for analyzing Whole Genome Duplication ('WGD') events. This package provides a user-friendly Shiny web application for non-experienced researchers to prepare input data and execute command lines for several well-known WGD analysis tools, including wgd', ksrates', i-ADHoRe', OrthoFinder', and Whale'. This package also provides the source code for experienced researchers to adjust and install the package to their own server. Key Features 1) Input Data Preparation This package allows users to conveniently upload and format their data, making it compatible with various WGD analysis tools. 2) Command Line Generation This package automatically generates the necessary command lines for selected WGD analysis tools, reducing manual errors and saving time. 3) Visualization This package offers interactive visualizations to explore and interpret WGD results, facilitating in-depth WGD analysis. 4) Comparative Genomics Users can study and compare WGD events across different species, aiding in evolutionary and comparative genomics studies. 5) User-Friendly Interface This Shiny web application provides an intuitive and accessible interface, making WGD analysis accessible to researchers and bioinformaticians of all levels.

r-smarterpoland 1.8.1
Propagated dependencies: r-rjson@0.2.23 r-jsonlite@2.0.0 r-httr@1.4.7 r-htmltools@0.5.8.1 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SmarterPoland
Licenses: GPL 3
Build system: r
Synopsis: Tools for Accessing Various Datasets Developed by the Foundation SmarterPoland.pl
Description:

This package provides tools for accessing and processing datasets prepared by the Foundation SmarterPoland.pl. Among all: access to API of Google Maps, Central Statistical Office of Poland, MojePanstwo, Eurostat, WHO and other sources.

r-simex 1.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: http://wolfganglederer.github.io/simex/
Licenses: GPL 3
Build system: r
Synopsis: SIMEX- And MCSIMEX-Algorithm for Measurement Error Models
Description:

Implementation of the SIMEX-Algorithm by Cook & Stefanski (1994) <doi:10.1080/01621459.1994.10476871> and MCSIMEX by Küchenhoff, Mwalili & Lesaffre (2006) <doi:10.1111/j.1541-0420.2005.00396.x>.

r-simriv 1.0.7
Propagated dependencies: r-terra@1.8-86 r-mco@1.17
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://www.r-project.org
Licenses: GPL 2+
Build system: r
Synopsis: Simulating Multistate Movements in River/Heterogeneous Landscapes
Description:

This package provides functions to generate and analyze spatially-explicit individual-based multistate movements in rivers, heterogeneous and homogeneous spaces. This is done by incorporating landscape bias on local behaviour, based on resistance rasters. Although originally conceived and designed to simulate trajectories of species constrained to linear habitats/dendritic ecological networks (e.g. river networks), the simulation algorithm is built to be highly flexible and can be applied to any (aquatic, semi-aquatic or terrestrial) organism, independently on the landscape in which it moves. Thus, the user will be able to use the package to simulate movements either in homogeneous landscapes, heterogeneous landscapes (e.g. semi-aquatic animal moving mainly along rivers but also using the matrix), or even in highly contrasted landscapes (e.g. fish in a river network). The algorithm and its input parameters are the same for all cases, so that results are comparable. Simulated trajectories can then be used as mechanistic null models (Potts & Lewis 2014, <DOI:10.1098/rspb.2014.0231>) to test a variety of Movement Ecology hypotheses (Nathan et al. 2008, <DOI:10.1073/pnas.0800375105>), including landscape effects (e.g. resources, infrastructures) on animal movement and species site fidelity, or for predictive purposes (e.g. road mortality risk, dispersal/connectivity). The package should be relevant to explore a broad spectrum of ecological phenomena, such as those at the interface of animal behaviour, management, landscape and movement ecology, disease and invasive species spread, and population dynamics.

r-secrfunc 1.0.0
Propagated dependencies: r-rcppparallel@5.1.11-1 r-rcppnumerical@0.6-0 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://www.otago.ac.nz/density/
Licenses: GPL 2+
Build system: r
Synopsis: Helper Functions for Package 'secr'
Description:

This package provides functions are provided for internal use by the spatial capture-recapture package secr (from version 5.4.0). The idea is to speed up the installation of secr', and possibly reduce its size. Initially the functions are those for area and transect search that use numerical integration code from RcppNumerical and RcppEigen'. The functions are not intended to be user-friendly and require considerable preprocessing of data.

r-sgt 2.0
Propagated dependencies: r-optimx@2025-4.9 r-numderiv@2016.8-1.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sgt
Licenses: GPL 3+
Build system: r
Synopsis: Skewed Generalized T Distribution Tree
Description:

Density, distribution function, quantile function and random generation for the skewed generalized t distribution. This package also provides a function that can fit data to the skewed generalized t distribution using maximum likelihood estimation.

r-select 1.5
Propagated dependencies: r-rsolnp@2.0.1 r-latticeextra@0.6-31 r-lattice@0.22-7 r-ade4@1.7-23
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=Select
Licenses: GPL 2+
Build system: r
Synopsis: Determines Species Probabilities Based on Functional Traits
Description:

The objective of these functions is to derive a species assemblage that satisfies a functional trait profile. Restoring resilient ecosystems requires a flexible framework for selecting assemblages that are based on the functional traits of species. However, current trait-based models have been limited to algorithms that can only select species by optimising specific trait values, and could not elegantly accommodate the common desire among restoration ecologists to produce functionally diverse assemblages. We have solved this problem by applying a non-linear optimisation algorithm that optimises Rao Q, a closed-form functional trait diversity index that incorporates species abundances, subject to other linear constraints. This framework generalises previous models that only optimised the entropy of the community, and can optimise both functional diversity and entropy simultaneously. This package can also be used to generate experimental assemblages to test the effects of community-level traits on community dynamics and ecosystem function. The method is based on theory discussed in Laughlin (2014, Ecology Letters) <doi:10.1111/ele.12288>.

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