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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-stripless 1.0-3
Propagated dependencies: r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=stripless
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Structured Trellis Displays Without Strips for Lattice Graphics
Description:

For making Trellis-type conditioning plots without strip labels. This is useful for displaying the structure of results from factorial designs and other studies when many conditioning variables would clutter the display with layers of redundant strip labels. Settings of the variables are encoded by layout and spacing in the trellis array and decoded by a separate legend. The functionality is implemented by a single S3 generic strucplot() function that is a wrapper for the Lattice package's xyplot() function. This allows access to all Lattice graphics capabilities in the usual way.

r-spearmanci 1.1
Propagated dependencies: r-mass@7.3-65 r-emplik@1.3-2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=spearmanCI
Licenses: GPL 3+
Build system: r
Synopsis: Jackknife Euclidean / Empirical Likelihood Inference for Spearman's Rho
Description:

This package provides functions for conducting jackknife Euclidean / empirical likelihood inference for Spearman's rho (de Carvalho and Marques (2012) <doi:10.1080/10920277.2012.10597644>).

r-syslognet 0.1.2.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/philaris/syslognet
Licenses: Expat
Build system: r
Synopsis: Send Log Messages to Remote 'syslog' Server
Description:

Send syslog protocol messages to a remote syslog server specified by host name and TCP network port.

r-sparktf 0.1.0
Propagated dependencies: r-sparklyr@1.9.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sparktf
Licenses: ASL 2.0
Build system: r
Synopsis: Interface for 'TensorFlow' 'TFRecord' Files with 'Apache Spark'
Description:

This package provides a sparklyr extension that enables reading and writing TensorFlow TFRecord files via Apache Spark'.

r-svdnf 0.1.11
Propagated dependencies: r-zoo@1.8-14 r-xts@0.14.1 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=SVDNF
Licenses: GPL 3
Build system: r
Synopsis: Discrete Nonlinear Filtering for Stochastic Volatility Models
Description:

This package implements the discrete nonlinear filter (DNF) of Kitagawa (1987) <doi:10.1080/01621459.1987.10478534> to a wide class of stochastic volatility (SV) models with return and volatility jumps following the work of Bégin and Boudreault (2021) <doi:10.1080/10618600.2020.1840995> to obtain likelihood evaluations and maximum likelihood parameter estimates. Offers several built-in SV models and a flexible framework for users to create customized models by specifying drift and diffusion functions along with an arrival distribution for the return and volatility jumps. Allows for the estimation of factor models with stochastic volatility (e.g., heteroskedastic volatility CAPM) by incorporating expected return predictors. Also includes functions to compute filtering and prediction distribution estimates, to simulate data from built-in and custom SV models with jumps, and to forecast future returns and volatility values using Monte Carlo simulation from a given SV model.

r-svydiags 0.7
Propagated dependencies: r-survey@4.4-8 r-matrix@1.7-4 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=svydiags
Licenses: GPL 3
Build system: r
Synopsis: Regression Model Diagnostics for Survey Data
Description:

Diagnostics for fixed effects linear and general linear regression models fitted with survey data. Extensions of standard diagnostics to complex survey data are included: standardized residuals, leverages, Cook's D, dfbetas, dffits, condition indexes, and variance inflation factors as found in Li and Valliant (Surv. Meth., 2009, 35(1), pp. 15-24; Jnl. of Off. Stat., 2011, 27(1), pp. 99-119; Jnl. of Off. Stat., 2015, 31(1), pp. 61-75); Liao and Valliant (Surv. Meth., 2012, 38(1), pp. 53-62; Surv. Meth., 2012, 38(2), pp. 189-202). Variance inflation factors and condition indexes are also computed for some general linear models as described in Liao (U. Maryland thesis, 2010).

r-surveygraph 1.0.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/surveygraph/surveygraphr
Licenses: Expat
Build system: r
Synopsis: Network Representations of Attitudes
Description:

This package provides a tool for computing network representations of attitudes, extracted from tabular data such as sociological surveys. Development of surveygraph software and training materials was initially funded by the European Union under the ERC Proof-of-concept programme (ERC, Attitude-Maps-4-All, project number: 101069264). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

r-sdtmval 0.4.1
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-stringr@1.6.0 r-rlang@1.1.6 r-readxl@1.4.5 r-purrr@1.2.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-knitr@1.50 r-haven@2.5.5 r-glue@1.8.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/skgithub14/sdtmval
Licenses: Expat
Build system: r
Synopsis: Validate SDTM Domains
Description:

This package provides a set of tools to assist statistical programmers in validating Study Data Tabulation Model (SDTM) domain data sets. Statistical programmers are required to validate that a SDTM data set domain has been programmed correctly, per the SDTM Implementation Guide (SDTMIG) by CDISC (<https://www.cdisc.org/standards/foundational/sdtmig>), study specification, and study protocol using a process called double programming. Double programming involves two different programmers independently converting the raw electronic data cut (EDC) data into a SDTM domain data table and comparing their results to ensure accurate standardization of the data. One of these attempts is termed production and the other validation'. Generally, production runs are the official programs for submittals and these are written in SAS'. Validation runs can be programmed in another language, in this case R'.

r-self 0.1.1
Propagated dependencies: r-xgboost@1.7.11.1 r-rcpp@1.1.0 r-data-table@1.17.8 r-comparecausalnetworks@0.2.6.2 r-bnlearn@5.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SELF
Licenses: GPL 2
Build system: r
Synopsis: Structural Equation Embedded Likelihood Framework for Causal Discovery
Description:

This package provides the SELF criteria to learn causal structure. Please cite "Ruichu Cai, Jie Qiao, Zhenjie Zhang, Zhifeng Hao. SELF: Structural Equational Embedded Likelihood Framework for Causal Discovery. AAAI. 2018.".

r-sequencespikeslab 1.0.1
Propagated dependencies: r-selectiveinference@1.2.5 r-rcppprogress@0.4.2 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=SequenceSpikeSlab
Licenses: GPL 2+
Build system: r
Synopsis: Exact Bayesian Model Selection Methods for the Sparse Normal Sequence Model
Description:

This package contains fast functions to calculate the exact Bayes posterior for the Sparse Normal Sequence Model, implementing the algorithms described in Van Erven and Szabo (2021, <doi:10.1214/20-BA1227>). For general hierarchical priors, sample sizes up to 10,000 are feasible within half an hour on a standard laptop. For beta-binomial spike-and-slab priors, a faster algorithm is provided, which can handle sample sizes of 100,000 in half an hour. In the implementation, special care has been taken to assure numerical stability of the methods even for such large sample sizes.

r-shinyoauth 0.3.0
Propagated dependencies: r-shiny@1.11.1 r-s7@0.2.1 r-rlang@1.1.6 r-r6@2.6.1 r-openssl@2.3.4 r-jsonlite@2.0.0 r-jose@1.2.1 r-httr2@1.2.1 r-htmltools@0.5.8.1 r-cli@3.6.5 r-cachem@1.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/lukakoning/shinyOAuth
Licenses: Expat
Build system: r
Synopsis: Provider-Agnostic OAuth Authentication for 'shiny' Applications
Description:

This package provides a simple, configurable, provider-agnostic OAuth 2.0 and OpenID Connect (OIDC) authentication framework for shiny applications using S7 classes. Defines providers, clients, and tokens, as well as various supporting functions and a shiny module. Features include cross-site request forgery (CSRF) protection, state encryption, Proof Key for Code Exchange (PKCE) handling, validation of OIDC identity tokens (nonces, signatures, claims), automatic user info retrieval, asynchronous flows, and hooks for audit logging.

r-soilconservation 1.0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SoilConservation
Licenses: GPL 3
Build system: r
Synopsis: Soil and Water Conservation
Description:

Includes four functions: RFactor_calc(), RFactor_est(), KFactor() and SoilLoss(). The rainfall erosivity factors can be calculated or estimated, and soil erodibility will be estimated by the equation extracted from the monograph. Soil loss will be estimated by the product of five factors (rainfall erosivity, soil erodibility, length and steepness slope, cover-management factor and support practice factor. In the future, additional functions can be included. This efforts to advance research in soil and water conservation, with fast and accurate results.

r-scbursts 1.6
Propagated dependencies: r-tibble@3.3.0 r-readxl@1.4.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=scbursts
Licenses: LGPL 2.1
Build system: r
Synopsis: Single Channel Bursts Analysis
Description:

This package provides tools to import and export from several existing pieces of ion-channel analysis software such as TAC', QUB', SCAN', and Clampfit', implements procedures such as dwell-time correction and defining bursts with a critical time, and provides tools for analysis of bursts, such as tools for sorting and plotting.

r-sparsefunclust 1.0.0
Propagated dependencies: 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=SparseFunClust
Licenses: GPL 3+
Build system: r
Synopsis: Sparse Functional Clustering
Description:

This package provides a general framework for performing sparse functional clustering as originally described in Floriello and Vitelli (2017) <doi:10.1016/j.jmva.2016.10.008>, with the possibility of jointly handling data misalignment (see Vitelli, 2019, <doi:10.48550/arXiv.1912.00687>).

r-stratifiedrf 0.2.2
Propagated dependencies: r-dplyr@1.1.4 r-c50@0.2.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=StratifiedRF
Licenses: GPL 3
Build system: r
Synopsis: Builds Trees by Sampling Variables in Groups
Description:

Random Forest-like tree ensemble that works with groups of predictor variables. When building a tree, a number of variables is taken randomly from each group separately, thus ensuring that it considers variables from each group for the splits. Useful when rows contain information about different things (e.g. user information and product information) and it's not sensible to make a prediction with information from only one group of variables, or when there are far more variables from one group than the other and it's desired to have groups appear evenly on trees. Trees are grown using the C5.0 algorithm rather than the usual CART algorithm. Supports parallelization (multithreaded), missing values in predictors, and categorical variables (without doing One-Hot encoding in the processing). Can also be used to create a regular (non-stratified) Random Forest-like model, but made up of C5.0 trees and with some additional control options. As it's built with C5.0 trees, it works only for classification (not for regression).

r-surrogaterank 2.2
Propagated dependencies: r-pbmcapply@1.5.1 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=SurrogateRank
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Rank-Based Test to Evaluate a Surrogate Marker
Description:

Uses a novel rank-based nonparametric approach to evaluate a surrogate marker in a small sample size setting. Details are described in Parast et al (2024) <doi:10.1093/biomtc/ujad035> and Hughes A et al (2025) <doi:10.1002/sim.70241>. A tutorial for this package can be found at <https://www.laylaparast.com/surrogaterank> and a Shiny App implementing the package can be found at <https://parastlab.shinyapps.io/SurrogateRankApp/>.

r-shotgroups 0.8.4
Propagated dependencies: r-kernsmooth@2.23-26 r-compquadform@1.4.4 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=shotGroups
Licenses: GPL 2+
Build system: r
Synopsis: Analyze Shot Group Data
Description:

Analyzes shooting data with respect to group shape, precision, and accuracy. This includes graphical methods, descriptive statistics, and inference tests using standard, but also non-parametric and robust statistical methods. Implements distributions for radial error in bivariate normal variables. Works with files exported by OnTarget PC/TDS', Silver Mountain e-target, ShotMarker e-target, SIUS e-target, or Taran', as well as with custom data files in text format. Supports inference from range statistics such as extreme spread. Includes a set of web-based graphical user interfaces.

r-sweater 0.1.8
Propagated dependencies: r-rcpp@1.1.0 r-quanteda@4.3.1 r-purrr@1.2.0 r-proxy@0.4-27 r-liblinear@2.10-24 r-data-table@1.17.8 r-combinat@0.0-8 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/gesistsa/sweater
Licenses: GPL 3+
Build system: r
Synopsis: Speedy Word Embedding Association Test and Extras Using R
Description:

Conduct various tests for evaluating implicit biases in word embeddings: Word Embedding Association Test (Caliskan et al., 2017), <doi:10.1126/science.aal4230>, Relative Norm Distance (Garg et al., 2018), <doi:10.1073/pnas.1720347115>, Mean Average Cosine Similarity (Mazini et al., 2019) <arXiv:1904.04047>, SemAxis (An et al., 2018) <arXiv:1806.05521>, Relative Negative Sentiment Bias (Sweeney & Najafian, 2019) <doi:10.18653/v1/P19-1162>, and Embedding Coherence Test (Dev & Phillips, 2019) <arXiv:1901.07656>.

r-seirfansy 1.1.1
Propagated dependencies: r-scales@1.4.0 r-rlang@1.1.6 r-pbapply@1.7-4 r-patchwork@1.3.2 r-magrittr@2.0.4 r-knitr@1.50 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-desctools@0.99.60 r-arm@1.14-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/umich-biostatistics/SEIRfansy
Licenses: GPL 2
Build system: r
Synopsis: Extended Susceptible-Exposed-Infected-Recovery Model
Description:

Extended Susceptible-Exposed-Infected-Recovery Model for handling high false negative rate and symptom based administration of diagnostic tests. <doi:10.1101/2020.09.24.20200238>.

r-silviculture 0.2.0
Propagated dependencies: r-s7@0.2.1 r-rlang@1.1.6 r-lifecycle@1.0.4 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cidree.github.io/silviculture/
Licenses: GPL 3+
Build system: r
Synopsis: Utility Functions for Forest Inventory and Silviculture
Description:

Perform common dendrometry operations such as inventory preparing, and inventory data analysis.

r-subgxe 0.9.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/umich-cphds/subgxe
Licenses: GPL 3
Build system: r
Synopsis: Combine Multiple GWAS by Using Gene-Environment Interactions
Description:

Classical methods for combining summary data from genome-wide association studies (GWAS) only use marginal genetic effects and power can be compromised in the presence of heterogeneity. subgxe is a R package that implements p-value assisted subset testing for association (pASTA), a method developed by Yu et al. (2019) <doi:10.1159/000496867>. pASTA generalizes association analysis based on subsets by incorporating gene-environment interactions into the testing procedure.

r-shinyratings 0.1.0
Propagated dependencies: 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://cran.r-project.org/package=shinyRatings
Licenses: Expat
Build system: r
Synopsis: An Intuitive Way of Providing Star Rating in a 'shiny' App
Description:

This package provides a simple interface to integrate star ratings into your shiny apps. It can be used for customer feedback systems, user reviews, or any application that requires user ratings. shinyRatings offers a straightforward and customisable solution that enhances user engagement and facilitates valuable feedback collection.

r-sar 1.0.4
Propagated dependencies: r-rcppparallel@5.1.11-1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-r6@2.6.1 r-matrix@1.7-4 r-jsonlite@2.0.0 r-httr@1.4.7 r-dplyr@1.1.4 r-azurestor@3.7.1 r-azurermr@2.4.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/hongooi73/SAR
Licenses: Expat
Build system: r
Synopsis: Smart Adaptive Recommendations
Description:

Smart Adaptive Recommendations (SAR) is the name of a fast, scalable, adaptive algorithm for personalized recommendations based on user transactions and item descriptions. It produces easily explainable/interpretable recommendations and handles "cold item" and "semi-cold user" scenarios. This package provides two implementations of SAR': a standalone implementation, and an interface to a web service in Microsoft's Azure cloud: <https://github.com/Microsoft/Product-Recommendations/blob/master/doc/sar.md>. The former allows fast and easy experimentation, and the latter provides robust scalability and extra features for production use.

r-structuraldecompose 0.1.1
Propagated dependencies: r-strucchange@1.5-4 r-segmented@2.1-4 r-changepoint@2.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://allen-1242.github.io/StructuralDecompose/
Licenses: Expat
Build system: r
Synopsis: Decomposes a Level Shifted Time Series
Description:

Explains the behavior of a time series by decomposing it into its trend, seasonality and residuals. It is built to perform very well in the presence of significant level shifts. It is designed to play well with any breakpoint algorithm and any smoothing algorithm. Currently defaults to lowess for smoothing and strucchange for breakpoint identification. The package is useful in areas such as trend analysis, time series decomposition, breakpoint identification and anomaly detection.

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