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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-eegkit 1.0-5
Propagated dependencies: r-signal@1.8-1 r-rgl@1.3.31 r-ica@1.0-3 r-eegkitdata@1.1 r-bigsplines@1.1-1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=eegkit
Licenses: GPL 2+
Build system: r
Synopsis: Toolkit for Electroencephalography Data
Description:

Analysis and visualization tools for electroencephalography (EEG) data. Includes functions for (i) plotting EEG data, (ii) filtering EEG data, (iii) smoothing EEG data; (iv) frequency domain (Fourier) analysis of EEG data, (v) Independent Component Analysis of EEG data, and (vi) simulating event-related potential EEG data.

r-exactltre 0.1.2
Propagated dependencies: r-popdemo@1.3-2 r-matrixcalc@1.0-6
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=exactLTRE
Licenses: Expat
Build system: r
Synopsis: An Exact Method for Life Table Response Experiment (LTRE) Analysis
Description:

Life Table Response Experiments (LTREs) are a method of comparative demographic analysis. The purpose is to quantify how the difference or variance in vital rates (stage-specific survival, growth, and fertility) among populations contributes to difference or variance in the population growth rate, "lambda." We provide functions for one-way fixed design and random design LTRE, using either the classical methods that have been in use for several decades, or an fANOVA-based exact method that directly calculates the impact on lambda of changes in matrix elements, for matrix elements and their interactions. The equations and descriptions for the classical methods of LTRE analysis can be found in Caswell (2001, ISBN: 0878930965), and the fANOVA-based exact methods are described in Hernandez et al. (2023) <doi:10.1111/2041-210X.14065>. We also provide some demographic functions, including generation time from Bienvenu and Legendre (2015) <doi:10.1086/681104>. For implementation of exactLTRE where all possible interactions are calculated, we use an operator matrix presented in Poelwijk, Krishna, and Ranganathan (2016) <doi:10.1371/journal.pcbi.1004771>.

r-eq5d 0.16.2
Propagated dependencies: r-rlang@1.1.6 r-lifecycle@1.0.4
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/fragla/eq5d
Licenses: Expat
Build system: r
Synopsis: Methods for Analysing 'EQ-5D' Data and Calculating 'EQ-5D' Index Scores
Description:

EQ-5D is a popular health related quality of life instrument used in the clinical and economic evaluation of health care. Developed by the EuroQol group <https://euroqol.org/>, the instrument consists of two components: health state description and evaluation. For the description component a subject self-rates their health in terms of five dimensions; mobility, self-care, usual activities, pain/discomfort, and anxiety/depression using either a three-level (EQ-5D-3L, <https://euroqol.org/information-and-support/euroqol-instruments/eq-5d-3l/>) or a five-level (EQ-5D-5L, <https://euroqol.org/information-and-support/euroqol-instruments/eq-5d-5l/>) scale. Frequently the scores on these five dimensions are converted to a single utility index using country specific value sets, which can be used in the clinical and economic evaluation of health care as well as in population health surveys. The eq5d package provides methods to calculate index scores from a subject's dimension scores. 33 TTO and 11 VAS EQ-5D-3L value sets including those for countries in Szende et al (2007) <doi:10.1007/1-4020-5511-0> and Szende et al (2014) <doi:10.1007/978-94-007-7596-1>, 48 EQ-5D-5L EQ-VT value sets, the EQ-5D-5L crosswalk value sets developed by van Hout et al. (2012) <doi:10.1016/j.jval.2012.02.008>, the crosswalk value sets for Bermuda, Jordan and Russia and the van Hout (2021) reverse crosswalk value sets. 12 EQ-5D-Y3L value sets are also included as are the NICE DSU age-sex based EQ-5D-3L to EQ-5D-5L and EQ-5D-5L to EQ-5D-3L mappings. Methods are also included for the analysis of EQ-5D profiles, including those from the book "Methods for Analyzing and Reporting EQ-5D data" by Devlin et al. (2020) <doi:10.1007/978-3-030-47622-9>. Additionally a shiny web tool is included to enable the calculation, visualisation and automated statistical analysis of EQ-5D data via a web browser using EQ-5D dimension scores stored in CSV or Excel files.

r-encompasstest 0.22
Propagated dependencies: r-pracma@2.4.6
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=EncompassTest
Licenses: GPL 3+
Build system: r
Synopsis: Direct Multi-Step Forecast Based Comparison of Nested Models via an Encompassing Test
Description:

The encompassing test is developed based on multi-step-ahead predictions of two nested models as in Pitarakis, J. (2023) <doi:10.48550/arXiv.2312.16099>. The statistics are standardised to a normal distribution, and the null hypothesis is that the larger model contains no additional useful information. P-values will be provided in the output.

r-emjmcmc 1.5.0
Propagated dependencies: r-withr@3.0.2 r-stringi@1.8.7 r-speedglm@0.3-5 r-hash@2.2.6.3 r-glmnet@4.1-10 r-bigmemory@4.6.4 r-biglm@0.9-3 r-bas@2.0.2
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=EMJMCMC
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Evolutionary Mode Jumping Markov Chain Monte Carlo Expert Toolbox
Description:

Implementation of the Mode Jumping Markov Chain Monte Carlo algorithm from Hubin, A., Storvik, G. (2018) <doi:10.1016/j.csda.2018.05.020>, Genetically Modified Mode Jumping Markov Chain Monte Carlo from Hubin, A., Storvik, G., & Frommlet, F. (2020) <doi:10.1214/18-BA1141>, Hubin, A., Storvik, G., & Frommlet, F. (2021) <doi:10.1613/jair.1.13047>, and Hubin, A., Heinze, G., & De Bin, R. (2023) <doi:10.3390/fractalfract7090641>, and Reversible Genetically Modified Mode Jumping Markov Chain Monte Carlo from Hubin, A., Frommlet, F., & Storvik, G. (2021) <doi:10.48550/arXiv.2110.05316>, which allow for estimating posterior model probabilities and Bayesian model averaging across a wide set of Bayesian models including linear, generalized linear, generalized linear mixed, generalized nonlinear, generalized nonlinear mixed, and logic regression models.

r-eurlex 0.4.9
Propagated dependencies: r-xml2@1.5.0 r-rvest@1.0.5 r-pdftools@3.6.0 r-httr@1.4.7 r-curl@7.0.0 r-antiword@1.3.4
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://michalovadek.github.io/eurlex/
Licenses: GPL 3
Build system: r
Synopsis: Retrieve Data on European Union Law
Description:

Access to data on European Union laws and court decisions made easy with pre-defined SPARQL queries and GET requests. See Ovadek (2021) <doi:10.1080/2474736X.2020.1870150> .

r-enshuman 1.0.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=enshuman
Licenses: LGPL 3+
Build system: r
Synopsis: Human Gene Annotation Data from 'Ensembl'
Description:

Gene information from Ensembl genome builds GRCh38.p14 and GRCh37.p13 to use with the topr package. The datasets were originally downloaded from <https://ftp.ensembl.org/pub/current/gtf/homo_sapiens/Homo_sapiens.GRCh38.111.gtf.gz> and <https://ftp.ensembl.org/pub/grch37/current/gtf/homo_sapiens/Homo_sapiens.GRCh37.87.gtf.gz> and converted into the format required by the topr package. See <https://github.com/totajuliusd/topr?tab=readme-ov-file#how-to-use-topr-with-other-species-than-human> to see the required format.

r-evola 1.0.7
Propagated dependencies: r-matrix@1.7-4 r-enhancer@1.1.0 r-crayon@1.5.3 r-alphasimr@2.1.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=evola
Licenses: GPL 2+
Build system: r
Synopsis: Evolutionary Algorithm
Description:

Runs an evolutionary algorithm using the AlphaSimR machinery <doi:10.1093/g3journal/jkaa017> .

r-evcombr 0.1-4
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=EvCombR
Licenses: GPL 3+
Build system: r
Synopsis: Evidence Combination in R
Description:

Combine pieces of evidence in the form of uncertainty representations.

r-eatgads 1.2.0
Propagated dependencies: r-tibble@3.3.0 r-stringi@1.8.7 r-plyr@1.8.9 r-hms@1.1.4 r-haven@2.5.5 r-eattools@0.7.9 r-eatdb@0.5.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/beckerbenj/eatGADS
Licenses: GPL 2+
Build system: r
Synopsis: Data Management of Large Hierarchical Data
Description:

Import SPSS data, handle and change SPSS meta data, store and access large hierarchical data in SQLite data bases.

r-egretci 2.0.5
Propagated dependencies: r-foreach@1.5.2 r-egret@3.0.11 r-binom@1.1-1.1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=EGRETci
Licenses: CC0
Build system: r
Synopsis: Exploration and Graphics for RivEr Trends Confidence Intervals
Description:

Collection of functions to evaluate uncertainty of results from water quality analysis using the Weighted Regressions on Time Discharge and Season (WRTDS) method. This package is an add-on to the EGRET package that performs the WRTDS analysis. The WRTDS modeling method was initially introduced and discussed in Hirsch et al. (2010) <doi:10.1111/j.1752-1688.2010.00482.x>, and expanded in Hirsch and De Cicco (2015) <doi:10.3133/tm4A10>. The paper describing the uncertainty and confidence interval calculations is Hirsch et al. (2015) <doi:10.1016/j.envsoft.2015.07.017>.

r-epinet 2.1.11
Propagated dependencies: r-network@1.19.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=epinet
Licenses: GPL 2
Build system: r
Synopsis: Epidemic/Network-Related Tools
Description:

This package provides a collection of epidemic/network-related tools. Simulates transmission of diseases through contact networks. Performs Bayesian inference on network and epidemic parameters, given epidemic data.

r-eigenmodel 1.12
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://pdhoff.github.io/
Licenses: GPL 2
Build system: r
Synopsis: Semiparametric Factor and Regression Models for Symmetric Relational Data
Description:

Estimation of the parameters in a model for symmetric relational data (e.g., the above-diagonal part of a square matrix), using a model-based eigenvalue decomposition and regression. Missing data is accommodated, and a posterior mean for missing data is calculated under the assumption that the data are missing at random. The marginal distribution of the relational data can be arbitrary, and is fit with an ordered probit specification. See Hoff (2007) <doi:10.48550/arXiv.0711.1146>. for details on the model.

r-evots 1.0.3
Propagated dependencies: r-pracma@2.4.6 r-plotly@4.11.0 r-paleots@0.6.2 r-mvtnorm@1.3-3 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://klvoje.github.io/evoTS/index.html
Licenses: GPL 2+
Build system: r
Synopsis: Analyses of Evolutionary Time-Series
Description:

Facilitates univariate and multivariate analysis of evolutionary sequences of phenotypic change. The package extends the modeling framework available in the paleoTS package. Please see <https://klvoje.github.io/evoTS/index.html> for information about the package and the implemented models.

r-effectplots 0.2.2
Propagated dependencies: r-scales@1.4.0 r-rcpp@1.1.0 r-plotly@4.11.0 r-patchwork@1.3.2 r-labeling@0.4.3 r-ggplot2@4.0.1 r-collapse@2.1.5
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/mayer79/effectplots
Licenses: GPL 3+
Build system: r
Synopsis: Effect Plots
Description:

High-performance implementation of various effect plots useful for regression and probabilistic classification tasks. The package includes partial dependence plots (Friedman, 2021, <doi:10.1214/aos/1013203451>), accumulated local effect plots and M-plots (both from Apley and Zhu, 2016, <doi:10.1111/rssb.12377>), as well as plots that describe the statistical associations between model response and features. It supports visualizations with either ggplot2 or plotly', and is compatible with most models, including Tidymodels', models wrapped in DALEX explainers, or models with case weights.

r-elections 1.0.1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=elections
Licenses: GPL 2+
Build system: r
Synopsis: USA Presidential Elections Data
Description:

This includes a dataset on the outcomes of the USA presidential elections since 1920, and various predictors, as used in <https://www.vanderwalresearch.com/blog/15-elections>.

r-educationr 0.1.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/lightbluetitan/educationr
Licenses: GPL 3
Build system: r
Synopsis: Comprehensive Collection of Educational Datasets
Description:

This package provides a comprehensive collection of datasets related to education, covering topics such as student performance, learning methods, test scores, absenteeism, and other educational metrics. This package serves as a resource for educational researchers, data analysts, and statisticians to explore and analyze data in the field of education.

r-ergm-ego 1.1.4
Propagated dependencies: r-tibble@3.3.0 r-survey@4.4-8 r-statnet-common@4.12.0 r-rdpack@2.6.4 r-rcolorbrewer@1.1-3 r-purrr@1.2.0 r-network@1.19.0 r-ergm@4.12.0 r-egor@1.25.10 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://statnet.org
Licenses: FSDG-compatible
Build system: r
Synopsis: Fit, Simulate and Diagnose Exponential-Family Random Graph Models to Egocentrically Sampled Network Data
Description:

Utilities for managing egocentrically sampled network data and a wrapper around the ergm package to facilitate ERGM inference and simulation from such data. See Krivitsky and Morris (2017) <doi:10.1214/16-AOAS1010>.

r-e2tree 0.2.0
Propagated dependencies: r-tidyr@1.3.1 r-rspectra@0.16-2 r-rpart-plot@3.1.4 r-rcpp@1.1.0 r-ranger@0.17.0 r-randomforest@4.7-1.2 r-purrr@1.2.0 r-partitions@1.10-9 r-matrix@1.7-4 r-ggplot2@4.0.1 r-future-apply@1.20.0 r-foreach@1.5.2 r-dplyr@1.1.4 r-doparallel@1.0.17 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/massimoaria/e2tree
Licenses: Expat
Build system: r
Synopsis: Explainable Ensemble Trees
Description:

The Explainable Ensemble Trees e2tree approach has been proposed by Aria et al. (2024) <doi:10.1007/s00180-022-01312-6>. It aims to explain and interpret decision tree ensemble models using a single tree-like structure. e2tree is a new way of explaining an ensemble tree trained through randomForest or xgboost packages.

r-easysurv 2.0.2
Propagated dependencies: r-usethis@3.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-survival@3.8-3 r-scales@1.4.0 r-rlang@1.1.6 r-purrr@1.2.0 r-plotly@4.11.0 r-parsnip@1.3.3 r-openxlsx@4.2.8.1 r-ggsurvfit@1.2.0 r-ggplot2@4.0.1 r-flexsurvcure@1.3.3 r-flexsurv@2.3.2 r-dplyr@1.1.4 r-data-table@1.17.8 r-cli@3.6.5 r-censored@0.3.3 r-bshazard@1.2
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/Maple-Health-Group/easysurv
Licenses: Expat
Build system: r
Synopsis: Simplify Survival Data Analysis and Model Fitting
Description:

Inspect survival data, plot Kaplan-Meier curves, assess the proportional hazards assumption, fit parametric survival models, predict and plot survival and hazards, and export the outputs to Excel'. A simple interface for fitting survival models using flexsurv::flexsurvreg(), flexsurv::flexsurvspline(), flexsurvcure::flexsurvcure(), and survival::survreg().

r-easypower 1.0.2
Propagated dependencies: r-pwr@1.3-0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=easypower
Licenses: GPL 3+
Build system: r
Synopsis: Sample Size Estimation for Experimental Designs
Description:

Power analysis is used in the estimation of sample sizes for experimental designs. Most programs and R packages will only output the highest recommended sample size to the user. Often the user input can be complicated and computing multiple power analyses for different treatment comparisons can be time consuming. This package simplifies the user input and allows the user to view all of the sample size recommendations or just the ones they want to see. The calculations used to calculate the recommended sample sizes are from the pwr package.

r-ercv 1.0.1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=ercv
Licenses: GPL 2+
Build system: r
Synopsis: Fitting Tails by the Empirical Residual Coefficient of Variation
Description:

This package provides a methodology simple and trustworthy for the analysis of extreme values and multiple threshold tests for a generalized Pareto distribution, together with an automatic threshold selection algorithm. See del Castillo, J, Daoudi, J and Lockhart, R (2014) <doi:10.1111/sjos.12037>.

r-easyahp 0.1.1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=easyAHP
Licenses: GPL 3
Build system: r
Synopsis: Analytic Hierarchy Process (AHP)
Description:

Given the scores from decision makers, the analytic hierarchy process can be conducted easily.

r-equatemultiple 1.1.3
Propagated dependencies: r-statmod@1.5.1 r-rcppdist@0.1.1.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-numderiv@2016.8-1.1 r-mvtnorm@1.3-3 r-matrix@1.7-4 r-equateirt@2.5.2 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=equateMultiple
Licenses: GPL 3
Build system: r
Synopsis: Equating of Multiple Forms
Description:

Equating of multiple forms using Item Response Theory (IRT) methods. See Battauz (2025) <doi:10.18637/jss.v115.i11> for a detailed description of the package. See Battauz M. (2017) <doi:10.1007/s11336-016-9517-x>, Battauz and Leoncio (2023) <doi:10.1177/01466216231151702> and Haberman S. J. (2009) <doi:10.1002/j.2333-8504.2009.tb02197.x>) for the methods to link multiple test forms.

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Total results: 69112