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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-evt0 1.1.5
Propagated dependencies: r-evd@2.3-7.1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=evt0
Licenses: GPL 2+
Build system: r
Synopsis: Mean of Order P, Peaks over Random Threshold Hill and High Quantile Estimates
Description:

The R package proposes extreme value index estimators for heavy tailed models by mean of order p <DOI:10.1016/j.csda.2012.07.019>, peaks over random threshold <DOI:10.57805/revstat.v4i3.37> and a bias-reduced estimator <DOI:10.1080/00949655.2010.547196>. The package also computes moment, generalised Hill <DOI:10.2307/3318416> and mixed moment estimates for the extreme value index. High quantiles and value at risk estimators based on these estimators are implemented.

r-eiopar 0.1.1
Propagated dependencies: r-jsonlite@2.0.0 r-httr@1.4.7 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=eiopaR
Licenses: Expat
Build system: r
Synopsis: Access to RFR (Risk-Free Rate) Curves Produced by the EIOPA
Description:

This package provides EIOPA (European Insurance And Occupational Pensions Authority) risk-free rates. Please note that the author of this package is not affiliated with EIOPA. The data is accessed through a REST API available at <https://mehdiechchelh.com/api/>.

r-ebchs 0.1.1
Propagated dependencies: r-pracma@2.4.6 r-fda@6.3.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/dulilun/EBCHS
Licenses: Expat
Build system: r
Synopsis: An Empirical Bayes Method for Chi-Squared Data
Description:

We provide the main R functions to compute the posterior interval for the noncentrality parameter of the chi-squared distribution. The skewness estimate of the posterior distribution is also available to improve the coverage rate of posterior intervals. Details can be found in Du and Hu (2022) <doi:10.1080/01621459.2020.1777137>.

r-easyverification 0.4.5
Propagated dependencies: r-specsverification@0.5-3 r-rcpp@1.1.0 r-pbapply@1.7-4
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://www.meteoswiss.admin.ch
Licenses: GPL 3
Build system: r
Synopsis: Ensemble Forecast Verification for Large Data Sets
Description:

Set of tools to simplify application of atomic forecast verification metrics for (comparative) verification of ensemble forecasts to large data sets. The forecast metrics are imported from the SpecsVerification package, and additional forecast metrics are provided with this package. Alternatively, new user-defined forecast scores can be implemented using the example scores provided and applied using the functionality of this package.

r-eegkitdata 1.1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=eegkitdata
Licenses: GPL 2+
Build system: r
Synopsis: Electroencephalography Toolkit Datasets
Description:

This package contains the example EEG data used in the package eegkit. Also contains code for easily creating larger EEG datasets from the EEG Database on the UCI Machine Learning Repository.

r-episimr 1.1
Propagated dependencies: r-shinythemes@1.2.0 r-shiny@1.11.1 r-openxlsx@4.2.8.1 r-dt@0.34.0 r-dplyr@1.1.4 r-desolve@1.40
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=EpiSimR
Licenses: GPL 3+
Build system: r
Synopsis: 'Shiny' App to Simulate the Dynamics of Epidemic and Endemic Diseases Spread
Description:

The EpiSimR package provides an interactive shiny app based on deterministic compartmental mathematical modeling for simulating and visualizing the dynamics of epidemic and endemic disease spread. It allows users to explore various intervention strategies, including vaccination and isolation, by adjusting key epidemiological parameters. The methodology follows the approach described by Brauer (2008) <doi:10.1007/978-3-540-78911-6_2>. Thanks to shiny package.

r-epireport 1.0.4
Propagated dependencies: r-zoo@1.8-14 r-tidyselect@1.2.1 r-tidyr@1.3.1 r-png@0.1-8 r-officer@0.7.1 r-ggplot2@4.0.1 r-flextable@0.9.10 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=EpiReport
Licenses: FSDG-compatible
Build system: r
Synopsis: Epidemiological Report
Description:

Drafting an epidemiological report in Microsoft Word format for a given disease, similar to the Annual Epidemiological Reports published by the European Centre for Disease Prevention and Control. Through standalone functions, it is specifically designed to generate each disease specific output presented in these reports and includes: - Table with the distribution of cases by Member State over the last five years; - Seasonality plot with the distribution of cases at the European Union / European Economic Area level, by month, over the past five years; - Trend plot with the trend and number of cases at the European Union / European Economic Area level, by month, over the past five years; - Age and gender bar graph with the distribution of cases at the European Union / European Economic Area level. Two types of datasets can be used: - The default dataset of dengue 2015-2019 data; - Any dataset specified as described in the vignette.

r-epiworldr 0.12.0.0
Propagated dependencies: r-cpp11@0.5.2
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/UofUEpiBio/epiworldR
Licenses: Expat
Build system: r
Synopsis: Fast Agent-Based Epi Models
Description:

This package provides a flexible framework for Agent-Based Models (ABM), the epiworldR package provides methods for prototyping disease outbreaks and transmission models using a C++ backend, making it very fast. It supports multiple epidemiological models, including the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Removed (SIR), Susceptible-Exposed-Infected-Removed (SEIR), and others, involving arbitrary mitigation policies and multiple-disease models. Users can specify infectiousness/susceptibility rates as a function of agents features, providing great complexity for the model dynamics. Furthermore, epiworldR is ideal for simulation studies featuring large populations.

r-elosteepness 0.5.0
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-elorating@0.46.18 r-bh@1.87.0-1 r-anidom@0.1.5
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/gobbios/EloSteepness
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Dominance Hierarchy Steepness via Elo Rating and David's Scores
Description:

Obtain Bayesian posterior distributions of dominance hierarchy steepness (Neumann and Fischer (2023) <doi:10.1111/2041-210X.14021>). Steepness estimation is based on Bayesian implementations of either Elo-rating or David's scores.

r-eventreport 0.1.1
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-scales@1.4.0 r-rlang@1.1.6 r-purrr@1.2.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/sebastianvanbaalen/eventreport
Licenses: FSDG-compatible
Build system: r
Synopsis: Diagnose, Visualize, and Aggregate Event Report Level Data
Description:

Diagnose, visualize, and aggregate event report level data to the event level. Users provide an event report level dataset, specify their aggregation rules, and the package produces a dataset aggregated at the event level. Also includes the Modes and Agents of Election-Related Violence in Côte d'Ivoire and Kenya (MAVERICK) dataset, an event report level dataset that records all documented instances of electoral violence from the first multiparty election to 2022 in Côte d'Ivoire (1995-2022) and Kenya (1992-2022).

r-efdm 0.2.2
Propagated dependencies: r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/mikkoku/efdm
Licenses: GPL 2
Build system: r
Synopsis: Simulate Forest Resources with the European Forestry Dynamics Model
Description:

An implementation of European Forestry Dynamics Model (EFDM) and an estimation algorithm for the transition probabilities. The EFDM is a large-scale forest model that simulates the development of the forest and estimates volume of wood harvested for any given forested area. This estimate can be broken down by, for example, species, site quality, management regime and ownership category. See Packalen et al. (2015) <doi:10.2788/153990>.

r-exams2learnr 0.1-0
Propagated dependencies: r-rmarkdown@2.30 r-learnr@0.11.6 r-knitr@1.50 r-exams@2.4-3
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://www.R-exams.org/
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Interface for 'exams' Exercises in 'learnr' Tutorials
Description:

Automatic generation of quizzes or individual questions for learnr tutorials based on R/exams exercises.

r-eixport 0.6.2
Propagated dependencies: r-sf@1.0-23 r-raster@3.6-32 r-ncdf4@1.24 r-data-table@1.17.8 r-cptcity@1.1.1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://atmoschem.github.io/eixport/
Licenses: Expat
Build system: r
Synopsis: Export Emissions to Atmospheric Models
Description:

Emissions are the mass of pollutants released into the atmosphere. Air quality models need emissions data, with spatial and temporal distribution, to represent air pollutant concentrations. This package, eixport, creates inputs for the air quality models WRF-Chem Grell et al (2005) <doi:10.1016/j.atmosenv.2005.04.027>, MUNICH Kim et al (2018) <doi:10.5194/gmd-11-611-2018> , BRAMS-SPM Freitas et al (2005) <doi:10.1016/j.atmosenv.2005.07.017> and RLINE Snyder et al (2013) <doi:10.1016/j.atmosenv.2013.05.074>. See the eixport website (<https://atmoschem.github.io/eixport/>) for more information, documentations and examples. More details in Ibarra-Espinosa et al (2018) <doi:10.21105/joss.00607>.

r-edgar 2.0.8
Propagated dependencies: r-xml@3.99-0.20 r-tm@0.7-16 r-stringr@1.6.0 r-stringi@1.8.7 r-r-utils@2.13.0 r-qdapregex@0.7.10 r-httr@1.4.7
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=edgar
Licenses: GPL 2
Build system: r
Synopsis: Tool for the U.S. SEC EDGAR Retrieval and Parsing of Corporate Filings
Description:

In the USA, companies file different forms with the U.S. Securities and Exchange Commission (SEC) through EDGAR (Electronic Data Gathering, Analysis, and Retrieval system). The EDGAR database automated system collects all the different necessary filings and makes it publicly available. This package facilitates retrieving, storing, searching, and parsing of all the available filings on the EDGAR server. It downloads filings from SEC server in bulk with a single query. Additionally, it provides various useful functions: extracts 8-K triggering events, extract "Business (Item 1)" and "Management's Discussion and Analysis(Item 7)" sections of annual statements, searches filings for desired keywords, provides sentiment measures, parses filing header information, and provides HTML view of SEC filings.

r-ez-combat 1.0.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=ez.combat
Licenses: Artistic License 2.0
Build system: r
Synopsis: Easy ComBat Harmonization
Description:

This package provides a dataframe-friendly implementation of ComBat Harmonization which uses an empirical Bayesian framework to remove batch effects. Johnson WE & Li C (2007) <doi:10.1093/biostatistics/kxj037> "Adjusting batch effects in microarray expression data using empirical Bayes methods." Fortin J-P, Cullen N, Sheline YI, Taylor WD, Aselcioglu I, Cook PA, Adams P, Cooper C, Fava M, McGrath PJ, McInnes M, Phillips ML, Trivedi MH, Weissman MM, & Shinohara RT (2017) <doi:10.1016/j.neuroimage.2017.11.024> "Harmonization of cortical thickness measurements across scanners and sites." Fortin J-P, Parker D, Tun<e7> B, Watanabe T, Elliott MA, Ruparel K, Roalf DR, Satterthwaite TD, Gur RC, Gur RE, Schultz RT, Verma R, & Shinohara RT (2017) <doi:10.1016/j.neuroimage.2017.08.047> "Harmonization of multi-site diffusion tensor imaging data.".

r-equivalencetest 0.0.1.1
Propagated dependencies: r-rootsolve@1.8.2.4 r-rdpack@2.6.4 r-polynom@1.4-1 r-cubature@2.1.4-1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=equivalenceTest
Licenses: GPL 3
Build system: r
Synopsis: Equivalence Test for the Means of Two Normal Distributions
Description:

Two methods for performing equivalence test for the means of two (test and reference) normal distributions are implemented. The null hypothesis of the equivalence test is that the absolute difference between the two means are greater than or equal to the equivalence margin and the alternative is that the absolute difference is less than the margin. Given that the margin is often difficult to obtain a priori, it is assumed to be a constant multiple of the standard deviation of the reference distribution. The first method assumes a fixed margin which is a constant multiple of the estimated standard deviation of the reference data and whose variability is ignored. The second method takes into account the margin variability. In addition, some tools to summarize and illustrate the data and test results are included to facilitate the evaluation of the data and interpretation of the results.

r-eply 0.1.2
Propagated dependencies: r-magrittr@2.0.4
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/wlandau/eply
Licenses: GPL 3
Build system: r
Synopsis: Apply a Function Over Expressions
Description:

Evaluate a function over a data frame of expressions.

r-eztune 3.1.1
Propagated dependencies: r-rpart@4.1.24 r-rocr@1.0-11 r-optimx@2025-4.9 r-glmnet@4.1-10 r-gbm@2.2.2 r-ga@3.2.4 r-e1071@1.7-16 r-biocstyle@2.38.0 r-ada@2.0-5
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=EZtune
Licenses: GPL 3
Build system: r
Synopsis: Tunes AdaBoost, Elastic Net, Support Vector Machines, and Gradient Boosting Machines
Description:

This package contains two functions that are intended to make tuning supervised learning methods easy. The eztune function uses a genetic algorithm or Hooke-Jeeves optimizer to find the best set of tuning parameters. The user can choose the optimizer, the learning method, and if optimization will be based on accuracy obtained through validation error, cross validation, or resubstitution. The function eztune.cv will compute a cross validated error rate. The purpose of eztune_cv is to provide a cross validated accuracy or MSE when resubstitution or validation data are used for optimization because error measures from both approaches can be misleading.

r-ertg3d 0.7.0
Propagated dependencies: r-tiff@0.1-12 r-rastervis@0.51.7 r-raster@3.6-32 r-plotly@4.11.0 r-pbapply@1.7-4 r-ggplot2@4.0.1 r-circstats@0.2-7
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://munterfi.github.io/eRTG3D/
Licenses: GPL 3
Build system: r
Synopsis: Empirically Informed Random Trajectory Generation in 3-D
Description:

This package creates realistic random trajectories in a 3-D space between two given fix points, so-called conditional empirical random walks (CERWs). The trajectory generation is based on empirical distribution functions extracted from observed trajectories (training data) and thus reflects the geometrical movement characteristics of the mover. A digital elevation model (DEM), representing the Earth's surface, and a background layer of probabilities (e.g. food sources, uplift potential, waterbodies, etc.) can be used to influence the trajectories. Unterfinger M (2018). "3-D Trajectory Simulation in Movement Ecology: Conditional Empirical Random Walk". Master's thesis, University of Zurich. <https://www.geo.uzh.ch/dam/jcr:6194e41e-055c-4635-9807-53c5a54a3be7/MasterThesis_Unterfinger_2018.pdf>. Technitis G, Weibel R, Kranstauber B, Safi K (2016). "An algorithm for empirically informed random trajectory generation between two endpoints". GIScience 2016: Ninth International Conference on Geographic Information Science, 9, online. <doi:10.5167/uzh-130652>.

r-eirm 0.5
Propagated dependencies: r-shinydashboard@0.7.3 r-shinycssloaders@1.1.0 r-shiny@1.11.1 r-reshape2@1.4.5 r-readxl@1.4.5 r-optimx@2025-4.9 r-magrittr@2.0.4 r-lme4@1.1-37 r-ggplot2@4.0.1 r-ggeffects@2.3.1 r-blme@1.0-6
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/okanbulut/eirm
Licenses: GPL 3+
Build system: r
Synopsis: Explanatory Item Response Modeling for Dichotomous and Polytomous Items
Description:

Analysis of dichotomous and polytomous response data using the explanatory item response modeling framework, as described in Bulut, Gorgun, & Yildirim-Erbasli (2021) <doi:10.3390/psych3030023>, Stanke & Bulut (2019) <doi:10.21449/ijate.515085>, and De Boeck & Wilson (2004) <doi:10.1007/978-1-4757-3990-9>. Generalized linear mixed modeling is used for estimating the effects of item-related and person-related variables on dichotomous and polytomous item responses.

r-elliplot 1.3.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=elliplot
Licenses: Expat
Build system: r
Synopsis: Ellipse Summary Plot of Quantiles
Description:

Correlation chart of two set (x and y) of data. Using Quantiles. Visualize the effect of factor.

r-ensemblebma 5.1.8
Propagated dependencies: r-chron@2.3-62
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=ensembleBMA
Licenses: GPL 2+
Build system: r
Synopsis: Probabilistic Forecasting using Ensembles and Bayesian Model Averaging
Description:

Bayesian Model Averaging to create probabilistic forecasts from ensemble forecasts and weather observations <https://stat.uw.edu/sites/default/files/files/reports/2007/tr516.pdf>.

r-emur 2.6.0
Propagated dependencies: r-wrassp@1.0.6 r-v8@8.0.1 r-uuid@1.2-1 r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-shiny@1.11.1 r-rstudioapi@0.17.1 r-rsqlite@2.4.4 r-rlang@1.1.6 r-readr@2.1.6 r-purrr@1.2.0 r-mime@0.13 r-jsonlite@2.0.0 r-httr@1.4.7 r-httpuv@1.6.16 r-fs@1.6.6 r-dplyr@1.1.4 r-dbi@1.2.3 r-cli@3.6.5 r-base64enc@0.1-3
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/IPS-LMU/emuR
Licenses: GPL 2+
Build system: r
Synopsis: Main Package of the EMU Speech Database Management System
Description:

Provide the EMU Speech Database Management System (EMU-SDMS) with database management, data extraction, data preparation and data visualization facilities. See <https://ips-lmu.github.io/The-EMU-SDMS-Manual/> for more details.

r-eventdatar 0.3.1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://bupar.net/
Licenses: Expat
Build system: r
Synopsis: Event Data Repository
Description:

Event dataset repository including both real-life and artificial event logs. They can be used in combination with functionalities provided by the bupaR packages. Janssenswillen et al. (2020) <http://ceur-ws.org/Vol-2703/paperTD7.pdf>.

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