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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-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-simulariatools 3.1.0
Propagated dependencies: r-terra@1.8-86 r-scales@1.4.0 r-reticulate@1.44.1 r-lubridate@1.9.4 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://www.simularia.it/simulariatools/
Licenses: GPL 2+
Build system: r
Synopsis: Simularia Tools for the Analysis of Air Pollution Data
Description:

This package provides a set of tools developed at Simularia for Simularia, to help preprocessing and post-processing of meteorological and air quality data.

r-sstack 1.0.1
Propagated dependencies: r-randomforest@4.7-1.2 r-foreach@1.5.2 r-dplyr@1.1.4 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=Sstack
Licenses: GPL 3
Build system: r
Synopsis: Bootstrap Stacking of Random Forest Models for Heterogeneous Data
Description:

Generates and predicts a set of linearly stacked Random Forest models using bootstrap sampling. Individual datasets may be heterogeneous (not all samples have full sets of features). Contains support for parallelization but the user should register their cores before running. This is an extension of the method found in Matlock (2018) <doi:10.1186/s12859-018-2060-2>.

r-stepmixr 0.1.3
Propagated dependencies: r-reticulate@1.44.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/Labo-Lacourse/StepMixr
Licenses: GPL 2
Build system: r
Synopsis: Interface to 'Python' Package 'StepMix'
Description:

This is an interface for the Python package StepMix'. It is a Python package following the scikit-learn API for model-based clustering and generalized mixture modeling (latent class/profile analysis) of continuous and categorical data. StepMix handles missing values through Full Information Maximum Likelihood (FIML) and provides multiple stepwise Expectation-Maximization (EM) estimation methods based on pseudolikelihood theory. Additional features include support for covariates and distal outcomes, various simulation utilities, and non-parametric bootstrapping, which allows inference in semi-supervised and unsupervised settings. Software paper available at <doi:10.18637/jss.v113.i08>.

r-sombrero 1.5.0
Propagated dependencies: r-shiny@1.11.1 r-scatterplot3d@0.3-44 r-rlang@1.1.6 r-metr@0.18.3 r-markdown@2.0 r-interp@1.1-6 r-igraph@2.2.1 r-ggwordcloud@0.6.2 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://forge.inrae.fr/nathalie.villa-vialaneix/sombrero
Licenses: GPL 2+
Build system: r
Synopsis: SOM Bound to Realize Euclidean and Relational Outputs
Description:

The stochastic (also called on-line) version of the Self-Organising Map (SOM) algorithm is provided. Different versions of the algorithm are implemented, for numeric and relational data and for contingency tables as described, respectively, in Kohonen (2001) <isbn:3-540-67921-9>, Olteanu & Villa-Vialaneix (2005) <doi:10.1016/j.neucom.2013.11.047> and Cottrell et al (2004) <doi:10.1016/j.neunet.2004.07.010>. The package also contains many plotting features (to help the user interpret the results), can handle (and impute) missing values and is delivered with a graphical user interface based on shiny'.

r-shinydrive 0.1.5
Propagated dependencies: r-zip@2.3.3 r-yaml@2.3.10 r-shiny@1.11.1 r-r-utils@2.13.0 r-knitr@1.50 r-htmltools@0.5.8.1 r-dt@0.34.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=shinydrive
Licenses: GPL 3
Build system: r
Synopsis: File Sharing Shiny Module
Description:

Shiny module for easily sharing files between users. Admin can add, remove, edit and download file. User can only download file. It's also possible to manage files using R functions directly.

r-scam 1.2-21
Propagated dependencies: r-mgcv@1.9-4 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=scam
Licenses: GPL 2+
Build system: r
Synopsis: Shape Constrained Additive Models
Description:

Generalized additive models under shape constraints on the component functions of the linear predictor. Models can include multiple shape-constrained (univariate and bivariate) and unconstrained terms. Routines of the package mgcv are used to set up the model matrix, print, and plot the results. Multiple smoothing parameter estimation by the Generalized Cross Validation or similar. See Pya and Wood (2015) <doi:10.1007/s11222-013-9448-7> for an overview. A broad selection of shape-constrained smoothers, linear functionals of smooths with shape constraints, and Gaussian models with AR1 residuals.

r-silhouette 0.9.6
Propagated dependencies: r-lifecycle@1.0.4 r-ggpubr@0.6.2 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://kskbhat.github.io/Silhouette/
Licenses: GPL 2
Build system: r
Synopsis: Proximity Measure Based Diagnostics for Standard, Soft, and Multi-Way Clustering
Description:

Quantifies clustering quality by measuring both cohesion within clusters and separation between clusters. Implements advanced silhouette width computations for diverse clustering structures, including: simplified silhouette (Van der Laan et al., 2003) <doi:10.1080/0094965031000136012>, Probability of Alternative Cluster normalization methods (Raymaekers & Rousseeuw, 2022) <doi:10.1080/10618600.2022.2050249>, fuzzy clustering and silhouette diagnostics using membership probabilities (Campello & Hruschka, 2006; Menardi, 2011; Bhat & Kiruthika, 2024) <doi:10.1016/j.fss.2006.07.006>, <doi:10.1007/s11222-010-9169-0>, <doi:10.1080/23737484.2024.2408534>, and multi-way clustering extensions such as block and tensor clustering (Schepers et al., 2008; Bhat & Kiruthika, 2025) <doi:10.1007/s00357-008-9005-9>, <doi:10.21203/rs.3.rs-6973596/v1>. Provides tools for computation and visualization (Rousseeuw, 1987) <doi:10.1016/0377-0427(87)90125-7> to support robust and reproducible cluster diagnostics across standard, soft, and multi-way clustering settings.

r-sentopics 0.7.6
Propagated dependencies: r-rcppprogress@0.4.2 r-rcpphungarian@0.3 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-quanteda@4.3.1 r-generics@0.1.4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/odelmarcelle/sentopics
Licenses: GPL 3+
Build system: r
Synopsis: Tools for Joint Sentiment and Topic Analysis of Textual Data
Description:

This package provides a framework that joins topic modeling and sentiment analysis of textual data. The package implements a fast Gibbs sampling estimation of Latent Dirichlet Allocation (Griffiths and Steyvers (2004) <doi:10.1073/pnas.0307752101>) and Joint Sentiment/Topic Model (Lin, He, Everson and Ruger (2012) <doi:10.1109/TKDE.2011.48>). It offers a variety of helpers and visualizations to analyze the result of topic modeling. The framework also allows enriching topic models with dates and externally computed sentiment measures. A flexible aggregation scheme enables the creation of time series of sentiment or topical proportions from the enriched topic models. Moreover, a novel method jointly aggregates topic proportions and sentiment measures to derive time series of topical sentiment.

r-sctools 0.3.3.1
Propagated dependencies: r-tidyr@1.3.1 r-synth@1.1-9 r-stringr@1.6.0 r-purrr@1.2.0 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-future@1.68.0 r-furrr@0.3.1 r-dplyr@1.1.4 r-cvtools@0.3.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SCtools
Licenses: GPL 3
Build system: r
Synopsis: Extensions for Synthetic Controls Analysis
Description:

Extends the functionality of the package Synth as detailed in Abadie, Diamond, and Hainmueller (2011) <doi:10.18637/jss.v042.i13>. Includes generating and plotting placebos, post/pre-MSPE (Mean Squared Prediction Error) significance tests and plots, and calculating average treatment effects for multiple treated units.

r-tabulog 0.1.1
Propagated dependencies: r-yaml@2.3.10
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tabulog
Licenses: Expat
Build system: r
Synopsis: Parsing Semi-Structured Log Files into Tabular Format
Description:

Convert semi-structured log files (such as Apache access.log files) into a tabular format (data.frame) using a standard template system.

r-tsissm 1.0.2
Propagated dependencies: r-zoo@1.8-14 r-xts@0.14.1 r-viridislite@0.4.2 r-tsmethods@1.0.3 r-tsdistributions@1.0.3 r-tsaux@1.0.0 r-tmb@1.9.18 r-sandwich@3.1-1 r-rtmb@1.8 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-progressr@0.18.0 r-nloptr@2.2.1 r-future-apply@1.20.0 r-future@1.68.0 r-flextable@0.9.10 r-data-table@1.17.8 r-copula@1.1-7
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/tsmodels/tsissm
Licenses: GPL 2
Build system: r
Synopsis: Linear Innovations State Space Unobserved Components Model
Description:

Unobserved components time series model using the linear innovations state space representation (single source of error) with choice of error distributions and option for dynamic variance. Methods for estimation using automatic differentiation, automatic model selection and ensembling, prediction, filtering, simulation and backtesting. Based on the model described in Hyndman et al (2012) <doi:10.1198/jasa.2011.tm09771>.

r-testdesign 1.7.0
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-lpsolve@5.6.23 r-logitnorm@0.8.39 r-foreach@1.5.2 r-crayon@1.5.3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://choi-phd.github.io/TestDesign/
Licenses: GPL 2+
Build system: r
Synopsis: Optimal Test Design Approach to Fixed and Adaptive Test Construction
Description:

Uses the optimal test design approach by Birnbaum (1968, ISBN:9781593119348) and van der Linden (2018) <doi:10.1201/9781315117430> to construct fixed, adaptive, and parallel tests. Supports the following mixed-integer programming (MIP) solver packages: Rsymphony', highs', gurobi', lpSolve', and Rglpk'. The gurobi package is not available from CRAN; see <https://www.gurobi.com/downloads/>.

r-tinsel 0.0.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/nteetor/tinsel
Licenses: Expat
Build system: r
Synopsis: Transform Functions using Decorators
Description:

Instead of nesting function calls, annotate and transform functions using "#." comments.

r-tsensembler 0.1.0
Propagated dependencies: r-zoo@1.8-14 r-xts@0.14.1 r-xgboost@1.7.11.1 r-softimpute@1.4-3 r-rcpproll@0.3.1 r-ranger@0.17.0 r-pls@2.8-5 r-monmlp@1.1.5-1 r-kernlab@0.9-33 r-glmnet@4.1-10 r-gbm@2.2.2 r-foreach@1.5.2 r-earth@5.3.4 r-doparallel@1.0.17 r-cubist@0.5.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/vcerqueira/tsensembler
Licenses: GPL 2+
Build system: r
Synopsis: Dynamic Ensembles for Time Series Forecasting
Description:

This package provides a framework for dynamically combining forecasting models for time series forecasting predictive tasks. It leverages machine learning models from other packages to automatically combine expert advice using metalearning and other state-of-the-art forecasting combination approaches. The predictive methods receive a data matrix as input, representing an embedded time series, and return a predictive ensemble model. The ensemble use generic functions predict() and forecast() to forecast future values of the time series. Moreover, an ensemble can be updated using methods, such as update_weights() or update_base_models()'. A complete description of the methods can be found in: Cerqueira, V., Torgo, L., Pinto, F., and Soares, C. "Arbitrated Ensemble for Time Series Forecasting." to appear at: Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer International Publishing, 2017; and Cerqueira, V., Torgo, L., and Soares, C.: "Arbitrated Ensemble for Solar Radiation Forecasting." International Work-Conference on Artificial Neural Networks. Springer, 2017 <doi:10.1007/978-3-319-59153-7_62>.

r-trendlsw 1.0.6
Propagated dependencies: r-wavethresh@4.7.3 r-locits@1.7.8
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/EuanMcGonigle/TrendLSW
Licenses: GPL 3+
Build system: r
Synopsis: Wavelet Methods for Analysing Locally Stationary Time Series
Description:

Fitting models for, and simulation of, trend locally stationary wavelet (TLSW) time series models, which take account of time-varying trend and dependence structure in a univariate time series. The TLSW model, and its estimation, is described in McGonigle, Killick and Nunes (2022a) <doi:10.1111/jtsa.12643>, (2022b) <doi:10.1214/22-EJS2044>. Further information regarding the use of the package, along with detailed examples, can be found in McGonigle, Killick and Nunes (2025) <doi:10.18637/jss.v115.i10>. New users will likely want to start with the TLSW function.

r-tidyterra 1.0.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-terra@1.8-86 r-sf@1.0-23 r-scales@1.4.0 r-rlang@1.1.6 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-generics@0.1.4 r-dplyr@1.1.4 r-data-table@1.17.8 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://dieghernan.github.io/tidyterra/
Licenses: Expat
Build system: r
Synopsis: 'tidyverse' Methods and 'ggplot2' Helpers for 'terra' Objects
Description:

Extension of the tidyverse for SpatRaster and SpatVector objects of the terra package. It includes also new geom_ functions that provide a convenient way of visualizing terra objects with ggplot2'.

r-tidystringdist 0.1.4
Propagated dependencies: r-tibble@3.3.0 r-stringdist@0.9.15 r-rlang@1.1.6 r-attempt@0.3.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tidystringdist
Licenses: Expat
Build system: r
Synopsis: String Distance Calculation with Tidy Data Principles
Description:

Calculation of string distance following the tidy data principles. Built on top of the stringdist package.

r-telp 1.0.3
Propagated dependencies: r-wordcloud@2.6 r-tm@0.7-16 r-tcltk2@1.6.1 r-rcolorbrewer@1.1-3 r-gridextra@2.3 r-ggplot2@4.0.1 r-arulesviz@1.5.4 r-arules@1.7-11
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=TELP
Licenses: GPL 3+
Build system: r
Synopsis: Social Representation Theory Application: The Free Evocation of Words Technique
Description:

Using The Free Evocation of Words Technique method with some functions, this package will make a social representation and other analysis. The Free Evocation of Words Technique consists of collecting a number of words evoked by a subject facing exposure to an inducer term. The purpose of this technique is to understand the relationships created between words evoked by the individual and the inducer term. This technique is included in the theory of social representations, therefore, on the information transmitted by an individual, seeks to create a profile that define a social group.

r-telraamstats 1.1.2
Propagated dependencies: r-yaml@2.3.10 r-tidyr@1.3.1 r-scales@1.4.0 r-rlang@1.1.6 r-reshape2@1.4.5 r-purrr@1.2.0 r-paletteer@1.6.0 r-lubridate@1.9.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-config@0.3.2
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://annuaire.agistaterre.org/telraamStats/
Licenses: FSDG-compatible
Build system: r
Synopsis: Retrieval and Visualization of Mobility Data from 'Telraam' Sensors
Description:

Streamline the processing of Telraam data, sourced from open data mobility sensors. These tools range from data retrieval (without the need for API knowledge) to data visualization, including data preprocessing.

r-testanaapp 1.1.2
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-shinydashboard@0.7.3 r-shinycssloaders@1.1.0 r-shiny@1.11.1 r-semplot@1.1.7 r-rmarkdown@2.30 r-plotrix@3.8-13 r-openxlsx@4.2.8.1 r-officer@0.7.1 r-officedown@0.4.1 r-mirt@1.45.1 r-lordif@0.4.2 r-latticeextra@0.6-31 r-golem@0.5.1 r-ggplot2@4.0.1 r-flextable@0.9.10 r-estcrm@1.6 r-dt@0.34.0 r-dplyr@1.1.4 r-difr@6.1.0 r-cowplot@1.2.0 r-brucer@2026.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/jiangyouxiang/TestAnaAPP
Licenses: GPL 3+
Build system: r
Synopsis: 'shiny' App for Test Analysis and Visualization
Description:

This application provides exploratory and confirmatory factor analysis, classical test theory, unidimensional and multidimensional item response theory, and continuous item response model analysis, through the shiny interactive interface. In addition, it offers rich functionalities for visualizing and downloading results. Users can download figures, tables, and analysis reports via the interactive interface.

r-tai 0.2.2
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tAI
Licenses: GPL 2+
Build system: r
Synopsis: The tRNA Adaptation Index
Description:

This package provides functions and example files to calculate the tRNA adaptation index, a measure of the level of co-adaptation between the set of tRNA genes and the codon usage bias of protein-coding genes in a given genome. The methodology is described in dos Reis, Wernisch and Savva (2003) <doi:10.1093/nar/gkg897>, and dos Reis, Savva and Wernisch (2004) <doi:10.1093/nar/gkh834>.

r-topodistance 1.0.2
Propagated dependencies: r-sp@2.2-0 r-scales@1.4.0 r-rcolorbrewer@1.1-3 r-raster@3.6-32 r-plotly@4.11.0 r-gdistance@1.6.5
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=topoDistance
Licenses: GPL 3
Build system: r
Synopsis: Calculating Topographic Paths and Distances
Description:

This package provides a toolkit for calculating topographic distances and identifying and plotting topographic paths. Topographic distances can be calculated along shortest topographic paths (Wang (2009) <doi:10.1111/j.1365-294X.2009.04338.x>), weighted topographic paths (Zhan et al. (1993) <doi:10.1007/3-540-57207-4_29>), and topographic least cost paths (Wang and Summers (2010) <doi:10.1111/j.1365-294X.2009.04465.x>). Functions can map topographic paths on colored or hill shade maps and plot topographic cross sections (elevation profiles) for the paths.

r-tsgsis 0.1
Propagated dependencies: r-mass@7.3-65 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=TSGSIS
Licenses: GPL 2+
Build system: r
Synopsis: Two Stage-Grouped Sure Independence Screening
Description:

To provide a high dimensional grouped variable selection approach for detection of whole-genome SNP effects and SNP-SNP interactions, as described in Fang et al. (2017, under review).

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