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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-summariser 2.3.0
Propagated dependencies: r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/condwanaland/summariser
Licenses: GPL 3
Build system: r
Synopsis: Easy Calculation and Visualisation of Confidence Intervals
Description:

This package provides functions to speed up the exploratory analysis of simple datasets using dplyr'. Functions are provided to do the common tasks of calculating confidence intervals.

r-stabilizedregression 1.1
Propagated dependencies: r-r6@2.6.1 r-mass@7.3-65 r-glmnet@4.1-10 r-ggrepel@0.9.6 r-ggplot2@4.0.1 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=StabilizedRegression
Licenses: GPL 3
Build system: r
Synopsis: Stabilizing Regression and Variable Selection
Description:

This package contains an implementation of StabilizedRegression', a regression framework for heterogeneous data introduced in Pfister et al. (2021) <arXiv:1911.01850>. The procedure uses averaging to estimate a regression of a set of predictors X on a response variable Y by enforcing stability with respect to a given environment variable. The resulting regression leads to a variable selection procedure which allows to distinguish between stable and unstable predictors. The package further implements a visualization technique which illustrates the trade-off between stability and predictiveness of individual predictors.

r-sejmrp 1.3.4
Propagated dependencies: r-xml2@1.5.0 r-xml@3.99-0.20 r-tidyr@1.3.1 r-stringi@1.8.7 r-rvest@1.0.5 r-rpostgresql@0.7-8 r-factoextra@1.0.7 r-dplyr@1.1.4 r-dbi@1.2.3 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sejmRP
Licenses: GPL 2
Build system: r
Synopsis: An Information About Deputies and Votings in Polish Diet from Seventh to Eighth Term of Office
Description:

Set of functions that access information about deputies and votings in Polish diet from webpage <http://www.sejm.gov.pl>. The package was developed as a result of an internship in MI2 Group - <http://mi2.mini.pw.edu.pl>, Faculty of Mathematics and Information Science, Warsaw University of Technology.

r-statmatch 1.4.3
Propagated dependencies: r-survey@4.4-8 r-proxy@0.4-27 r-lpsolve@5.6.23 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/marcellodo/StatMatch
Licenses: GPL 2+
Build system: r
Synopsis: Statistical Matching or Data Fusion
Description:

Integration of two data sources referred to the same target population which share a number of variables. Some functions can also be used to impute missing values in data sets through hot deck imputation methods. Methods to perform statistical matching when dealing with data from complex sample surveys are available too.

r-shinycox 1.1.3
Propagated dependencies: r-survival@3.8-3 r-shiny@1.11.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/harryc598/shinyCox
Licenses: LGPL 3+
Build system: r
Synopsis: Create 'shiny' Applications for Cox Proportional Hazards Models
Description:

Takes one or more fitted Cox proportional hazards models and writes a shiny application to a directory specified by the user. The shiny application displays predicted survival curves based on user input, and contains none of the original data used to create the Cox model or models. The goal is towards visualization and presentation of predicted survival curves.

r-sfarrow 0.4.1
Propagated dependencies: r-sf@1.0-23 r-jsonlite@2.0.0 r-dplyr@1.1.4 r-arrow@22.0.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/wcjochem/sfarrow
Licenses: Expat
Build system: r
Synopsis: Read/Write Simple Feature Objects ('sf') with 'Apache' 'Arrow'
Description:

Support for reading/writing simple feature ('sf') spatial objects from/to Parquet files. Parquet files are an open-source, column-oriented data storage format from Apache (<https://parquet.apache.org/>), now popular across programming languages. This implementation converts simple feature list geometries into well-known binary format for use by arrow', and coordinate reference system information is maintained in a standard metadata format.

r-sppcomb 0.1
Propagated dependencies: r-nleqslv@3.3.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SPPcomb
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Combining Different Spatial Datasets in Cancer Risk Estimation
Description:

We propose a novel two-step procedure to combine epidemiological data obtained from diverse sources with the aim to quantify risk factors affecting the probability that an individual develops certain disease such as cancer. See Hui Huang, Xiaomei Ma, Rasmus Waagepetersen, Theodore R. Holford, Rong Wang, Harvey Risch, Lloyd Mueller & Yongtao Guan (2014) A New Estimation Approach for Combining Epidemiological Data From Multiple Sources, Journal of the American Statistical Association, 109:505, 11-23, <doi:10.1080/01621459.2013.870904>.

r-ssd4mosaic 1.0.4-2
Propagated dependencies: r-shinyjs@2.1.0 r-shinybusy@0.3.3 r-shiny@1.11.1 r-rmarkdown@2.30 r-rlang@1.1.6 r-rhandsontable@0.3.8 r-jsonlite@2.0.0 r-htmlwidgets@1.6.4 r-htmltools@0.5.8.1 r-golem@0.5.1 r-ggplot2@4.0.1 r-fitdistrplus@1.2-4 r-config@0.3.2 r-actuar@3.3-6
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://gitlab.in2p3.fr/mosaic-software/mosaic-ssd
Licenses: Expat
Build system: r
Synopsis: Web Application for the SSD Module of the MOSAIC Platform
Description:

Web application using shiny for the SSD (Species Sensitivity Distribution) module of the MOSAIC (MOdeling and StAtistical tools for ecotoxICology) platform. It estimates the Hazardous Concentration for x% of the species (HCx) from toxicity values that can be censored and provides various plotting options for a better understanding of the results. See our companion paper Kon Kam King et al. (2014) <doi:10.48550/arXiv.1311.5772>.

r-scriptname 1.0.1
Propagated dependencies: r-rlang@1.1.6 r-purrr@1.2.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/MullinsLab/scriptName
Licenses: Expat
Build system: r
Synopsis: Determine a Script's Filename from Within the Script Itself
Description:

This package provides a small set of functions wrapping up the call stack and command line inspection needed to determine a running script's filename from within the script itself.

r-simukde 1.3.0
Propagated dependencies: r-mvtnorm@1.3-3 r-mass@7.3-65 r-ks@1.15.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/galaamn/simukde
Licenses: GPL 3+ FSDG-compatible
Build system: r
Synopsis: Simulation with Kernel Density Estimation
Description:

Generates random values from a univariate and multivariate continuous distribution by using kernel density estimation based on a sample. Duong (2017) <doi:10.18637/jss.v021.i07>, Christian P. Robert and George Casella (2010 ISBN:978-1-4419-1575-7) <doi:10.1007/978-1-4419-1576-4>.

r-staninside 0.0.4
Propagated dependencies: r-rappdirs@0.3.3 r-fs@1.6.6 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/medewitt/staninside
Licenses: Expat
Build system: r
Synopsis: Facilitating the Use of 'Stan' Within Packages
Description:

Infrastructure and functions that can be used for integrating Stan (Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>) code into stand alone R packages which in turn use the CmdStan engine which is often accessed through CmdStanR'. Details given in Stan Development Team (2025) <https://mc-stan.org/cmdstanr/>. Using CmdStanR and pre-written Stan code can make package installation easy. Using staninside offers a way to cache user-compiled Stan models in user-specified directories reducing the need to recompile the same model multiple times.

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-summer 2.0.0
Propagated dependencies: r-viridis@0.6.5 r-terra@1.8-86 r-survival@3.8-3 r-survey@4.4-8 r-spdep@1.4-1 r-sp@2.2-0 r-shadowtext@0.1.6 r-sf@1.0-23 r-scales@1.4.0 r-reshape2@1.4.5 r-rcolorbrewer@1.1-3 r-matrix@1.7-4 r-lifecycle@1.0.4 r-haven@2.5.5 r-ggridges@0.5.7 r-ggplot2@4.0.1 r-fields@17.1 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/richardli/SUMMER
Licenses: GPL 2+
Build system: r
Synopsis: Small-Area-Estimation Unit/Area Models and Methods for Estimation in R
Description:

This package provides methods for spatial and spatio-temporal smoothing of demographic and health indicators using survey data, with particular focus on estimating and projecting under-five mortality rates, described in Mercer et al. (2015) <doi:10.1214/15-AOAS872>, Li et al. (2019) <doi:10.1371/journal.pone.0210645>, Wu et al. (DHS Spatial Analysis Reports No. 21, 2021), and Li et al. (2023) <doi:10.48550/arXiv.2007.05117>.

r-schoenberg 2.0.3
Propagated dependencies: r-crayon@1.5.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=schoenberg
Licenses: GPL 3+
Build system: r
Synopsis: Tools for 12-Tone Musical Composition
Description:

This package provides functions for creating and manipulating 12-tone (i.e., dodecaphonic) musical matrices using Arnold Schoenberg's (1923) serialism technique. This package can generate random 12-tone matrices and can generate matrices using a pre-determined sequence of notes.

r-stplanr 1.2.3
Propagated dependencies: r-sfheaders@0.4.5 r-sf@1.0-23 r-rlang@1.1.6 r-rcpp@1.1.0 r-pbapply@1.7-4 r-od@0.5.1 r-nabor@0.5.0 r-magrittr@2.0.4 r-lwgeom@0.2-14 r-jsonlite@2.0.0 r-httr@1.4.7 r-geosphere@1.5-20 r-dplyr@1.1.4 r-data-table@1.17.8 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/ropensci/stplanr
Licenses: Expat
Build system: r
Synopsis: Sustainable Transport Planning
Description:

This package provides tools for transport planning with an emphasis on spatial transport data and non-motorized modes. The package was originally developed to support the Propensity to Cycle Tool', a publicly available strategic cycle network planning tool (Lovelace et al. 2017) <doi:10.5198/jtlu.2016.862>, but has since been extended to support public transport routing and accessibility analysis (Moreno-Monroy et al. 2017) <doi:10.1016/j.jtrangeo.2017.08.012> and routing with locally hosted routing engines such as OSRM (Lowans et al. 2023) <doi:10.1016/j.enconman.2023.117337>. The main functions are for creating and manipulating geographic "desire lines" from origin-destination (OD) data (building on the od package); calculating routes on the transport network locally and via interfaces to routing services such as <https://cyclestreets.net/> (Desjardins et al. 2021) <doi:10.1007/s11116-021-10197-1>; and calculating route segment attributes such as bearing. The package implements the travel flow aggregration method described in Morgan and Lovelace (2020) <doi:10.1177/2399808320942779> and the OD jittering method described in Lovelace et al. (2022) <doi:10.32866/001c.33873>. Further information on the package's aim and scope can be found in the vignettes and in a paper in the R Journal (Lovelace and Ellison 2018) <doi:10.32614/RJ-2018-053>, and in a paper outlining the landscape of open source software for geographic methods in transport planning (Lovelace, 2021) <doi:10.1007/s10109-020-00342-2>.

r-sqlcaser 0.2.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sqlcaser
Licenses: Expat
Build system: r
Synopsis: 'SQL' Case Statement Generator
Description:

Includes built-in methods for generating long SQL CASE statements, and other SQL statements that may otherwise be arduous to construct by hand.The generated statement can easily be concatenated to string literals to form queries to SQL'-like databases, such as when using the RODBC package. The current methods include casewhen() for building CASE statements, inlist() for building IN statements, and updatetable() for building UPDATE statements.

r-simseq 1.4.0
Propagated dependencies: r-fdrtool@1.2.18
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SimSeq
Licenses: GPL 2+
Build system: r
Synopsis: Nonparametric Simulation of RNA-Seq Data
Description:

RNA sequencing analysis methods are often derived by relying on hypothetical parametric models for read counts that are not likely to be precisely satisfied in practice. Methods are often tested by analyzing data that have been simulated according to the assumed model. This testing strategy can result in an overly optimistic view of the performance of an RNA-seq analysis method. We develop a data-based simulation algorithm for RNA-seq data. The vector of read counts simulated for a given experimental unit has a joint distribution that closely matches the distribution of a source RNA-seq dataset provided by the user. Users control the proportion of genes simulated to be differentially expressed (DE) and can provide a vector of weights to control the distribution of effect sizes. The algorithm requires a matrix of RNA-seq read counts with large sample sizes in at least two treatment groups. Many datasets are available that fit this standard.

r-smoothy 1.0.0
Propagated dependencies: r-zoo@1.8-14 r-tidyr@1.3.1 r-stringr@1.6.0 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=smoothy
Licenses: GPL 3+
Build system: r
Synopsis: Automatic Estimation of the Most Likely Drug Combination using Smooth Algorithm
Description:

This package provides a flexible moving average algorithm for modeling drug exposure in pharmacoepidemiology studies as presented in the article: Ouchi, D., Giner-Soriano, M., Gómez-Lumbreras, A., Vedia Urgell, C.,Torres, F., & Morros, R. (2022). "Automatic Estimation of the Most Likely Drug Combination in Electronic Health Records Using the Smooth Algorithm : Development and Validation Study." JMIR medical informatics, 10(11), e37976. <doi:10.2196/37976>.

r-shutterplot 0.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=shutterplot
Licenses: GPL 3
Build system: r
Synopsis: The R Shutter Plot Package
Description:

Shows the scatter plot along with the fitted regression lines. It depicts min, max, the three quartiles, mean, and sd for each variable. It also depicts sd-line, sd-box, r, r-square, prediction boundaries, and regression outliers.

r-sld 1.0.1
Propagated dependencies: r-lmom@3.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/newystats/SLD/
Licenses: GPL 2+
Build system: r
Synopsis: Estimation and Use of the Quantile-Based Skew Logistic Distribution
Description:

The skew logistic distribution is a quantile-defined generalisation of the logistic distribution (van Staden and King 2015). Provides random numbers, quantiles, probabilities, densities and density quantiles for the distribution. It provides Quantile-Quantile plots and method of L-Moments estimation (including asymptotic standard errors) for the distribution.

r-ssmutpa 0.1.2
Propagated dependencies: r-survival@3.8-3 r-rcolorbrewer@1.1-3 r-pheatmap@1.0.13 r-nbclust@3.0.1 r-matrix@1.7-4 r-maftools@2.26.0 r-kernlab@0.9-33 r-igraph@2.2.1 r-ggridges@0.5.7 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=ssMutPA
Licenses: GPL 2+
Build system: r
Synopsis: Single-Sample Mutation-Based Pathway Analysis
Description:

This package provides a systematic bioinformatics tool to perform single-sample mutation-based pathway analysis by integrating somatic mutation data with the Protein-Protein Interaction (PPI) network. In this method, we use local and global weighted strategies to evaluate the effects of network genes from mutations according to the network topology and then calculate the mutation-based pathway enrichment score (ssMutPES) to reflect the accumulated effect of mutations of each pathway. Subsequently, the ssMutPES profiles are used for unsupervised spectral clustering to identify cancer subtypes.

r-semsens 1.5.5
Propagated dependencies: r-lavaan@0.6-20
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SEMsens
Licenses: GPL 3
Build system: r
Synopsis: Tool for Sensitivity Analysis in Structural Equation Modeling
Description:

Perform sensitivity analysis in structural equation modeling using meta-heuristic optimization methods (e.g., ant colony optimization and others). The references for the proposed methods are: (1) Leite, W., & Shen, Z., Marcoulides, K., Fish, C., & Harring, J. (2022). <doi:10.1080/10705511.2021.1881786> (2) Harring, J. R., McNeish, D. M., & Hancock, G. R. (2017) <doi:10.1080/10705511.2018.1506925>; (3) Fisk, C., Harring, J., Shen, Z., Leite, W., Suen, K., & Marcoulides, K. (2022). <doi:10.1177/00131644211073121>; (4) Socha, K., & Dorigo, M. (2008) <doi:10.1016/j.ejor.2006.06.046>. We also thank Dr. Krzysztof Socha for sharing his research on ant colony optimization algorithm with continuous domains and associated R code, which provided the base for the development of this package.

r-shinystoreplus 1.6
Propagated dependencies: r-shinywidgets@0.9.0 r-shiny@1.11.1 r-jsonlite@2.0.0 r-htmltools@0.5.8.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://shinystoreplus.obi.obianom.com
Licenses: Expat
Build system: r
Synopsis: Secure in-Browser and Database Storage for 'shiny' Inputs, Outputs, Views and User Likes
Description:

Store persistent and synchronized data from shiny inputs within the browser. Refresh shiny applications and preserve user-inputs over multiple sessions. A database-like storage format is implemented using Dexie.js <https://dexie.org>, a minimal wrapper for IndexedDB'. Transfer browser link parameters to shiny input or output values. Store app visitor views, likes and followers.

r-s4dm 0.0.1
Propagated dependencies: r-terra@1.8-86 r-sf@1.0-23 r-rvinecopulib@0.7.3.1.0 r-robust@0.7-5 r-rdpack@2.6.4 r-proc@1.19.0.1 r-np@0.60-18 r-mvtnorm@1.3-3 r-maxnet@0.1.4 r-kernlab@0.9-33 r-geometry@0.5.2 r-flexclust@1.5.0 r-dplyr@1.1.4 r-densratio@0.2.1 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=S4DM
Licenses: Expat
Build system: r
Synopsis: Small Sample Size Species Distribution Modeling
Description:

This package implements a set of distribution modeling methods that are suited to species with small sample sizes (e.g., poorly sampled species or rare species). While these methods can also be used on well-sampled taxa, they are united by the fact that they can be utilized with relatively few data points. More details on the currently implemented methodologies can be found in Drake and Richards (2018) <doi:10.1002/ecs2.2373>, Drake (2015) <doi:10.1098/rsif.2015.0086>, and Drake (2014) <doi:10.1890/ES13-00202.1>.

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