_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
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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-electivity 1.0.2
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/DesiQuintans/electivity
Licenses: Expat
Build system: r
Synopsis: Algorithms for Electivity Indices
Description:

This package provides all electivity algorithms (including Vanderploeg and Scavia electivity) that were examined in Lechowicz (1982) <doi:10.1007/BF00349007>, plus the example data that were provided for moth resource utilisation.

r-evclass 2.0.2
Propagated dependencies: r-r-utils@2.13.0 r-ibelief@1.3.1 r-fnn@1.1.4.1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=evclass
Licenses: GPL 3
Build system: r
Synopsis: Evidential Distance-Based Classification
Description:

Different evidential classifiers, which provide outputs in the form of Dempster-Shafer mass functions. The methods are: the evidential K-nearest neighbor rule, the evidential neural network, radial basis function neural networks, logistic regression, feed-forward neural networks.

r-edecob 1.2.2
Propagated dependencies: r-rlang@1.1.6 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=edecob
Licenses: Expat
Build system: r
Synopsis: Event Detection Using Confidence Bounds
Description:

Detects sustained change in digital bio-marker data using simultaneous confidence bands. Accounts for noise using an auto-regressive model. Based on Buehlmann (1998) "Sieve bootstrap for smoothing in nonstationary time series" <doi:10.1214/aos/1030563978>.

r-estprod 1.2
Propagated dependencies: r-minpack-lm@1.2-4 r-lazyeval@0.2.2 r-gmm@1.9-1 r-formula@1.2-5 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=estprod
Licenses: GPL 3
Build system: r
Synopsis: Estimation of Production Functions
Description:

Estimation of production functions by the Olley-Pakes, Levinsohn-Petrin and Wooldridge methodologies. The package aims to reproduce the results obtained with the Stata's user written opreg <http://www.stata-journal.com/article.html?article=st0145> and levpet <http://www.stata-journal.com/article.html?article=st0060> commands. The first was originally proposed by Olley, G.S. and Pakes, A. (1996) <doi:10.2307/2171831>. The second by Levinsohn, J. and Petrin, A. (2003) <doi:10.1111/1467-937X.00246>. And the third by Wooldridge (2009) <doi:10.1016/j.econlet.2009.04.026>.

r-exhaustiverasch 0.3.7
Propagated dependencies: r-tictoc@1.2.1 r-psychotree@0.16-2 r-psychotools@0.7-5 r-psych@2.5.6 r-pbapply@1.7-4 r-pairwise@0.6.2-0 r-erm@1.0-10 r-arrangements@1.1.9
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/chrgrebe/exhaustiveRasch
Licenses: GPL 3
Build system: r
Synopsis: Item Selection and Exhaustive Search for Rasch Models
Description:

Automation of the item selection processes for Rasch scales by means of exhaustive search for suitable Rasch models (dichotomous, partial credit, rating-scale) in a list of item-combinations. The item-combinations to test can be either all possible combinations or item-combinations can be defined by several rules (forced inclusion of specific items, exclusion of combinations, minimum/maximum items of a subset of items). Tests for model fit and item fit include ordering of the thresholds, item fit-indices, likelihood ratio test, Martin-Löf test, Wald-like test, person-item distribution, person separation index, principal components of Rasch residuals, empirical representation of all raw scores or Rasch trees for detecting differential item functioning. The tests, their ordering and their parameters can be defined by the user. For parameter estimation and model tests, functions of the packages eRm', psychotools or pairwise can be used.

r-edmdata 1.3.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://tmsalab.github.io/edmdata/
Licenses: Expat
Build system: r
Synopsis: Data Sets for Psychometric Modeling
Description:

Collection of data sets from various assessments that can be used to evaluate psychometric models. These data sets have been analyzed in the following papers that introduced new methodology as part of the application section: Jimenez, A., Balamuta, J. J., & Culpepper, S. A. (2023) <doi:10.1111/bmsp.12307>, Culpepper, S. A., & Balamuta, J. J. (2021) <doi:10.1080/00273171.2021.1985949>, Yinghan Chen et al. (2021) <doi:10.1007/s11336-021-09750-9>, Yinyin Chen et al. (2020) <doi:10.1007/s11336-019-09693-2>, Culpepper, S. A. (2019a) <doi:10.1007/s11336-019-09683-4>, Culpepper, S. A. (2019b) <doi:10.1007/s11336-018-9643-8>, Culpepper, S. A., & Chen, Y. (2019) <doi:10.3102/1076998618791306>, Culpepper, S. A., & Balamuta, J. J. (2017) <doi:10.1007/s11336-015-9484-7>, and Culpepper, S. A. (2015) <doi:10.3102/1076998615595403>.

r-ebgenotyping 2.0.1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=ebGenotyping
Licenses: GPL 2
Build system: r
Synopsis: Genotyping and SNP Detection using Next Generation Sequencing Data
Description:

Genotyping the population using next generation sequencing data is essentially important for the rare variant detection. In order to distinguish the genomic structural variation from sequencing error, we propose a statistical model which involves the genotype effect through a latent variable to depict the distribution of non-reference allele frequency data among different samples and different genome loci, while decomposing the sequencing error into sample effect and positional effect. An ECM algorithm is implemented to estimate the model parameters, and then the genotypes and SNPs are inferred based on the empirical Bayes method.

r-etasflp 2.2.2
Propagated dependencies: r-maps@3.4.3 r-mapdata@2.3.1 r-fields@17.1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=etasFLP
Licenses: GPL 2+
Build system: r
Synopsis: Mixed FLP and ML Estimation of ETAS Space-Time Point Processes for Earthquake Description
Description:

Estimation of the components of an ETAS (Epidemic Type Aftershock Sequence) model for earthquake description. Non-parametric background seismicity can be estimated through FLP (Forward Likelihood Predictive). New version 2.0.0: covariates have been introduced to explain the effects of external factors on the induced seismicity; the parametrization has been changed; Chiodi, Adelfio (2017)<doi:10.18637/jss.v076.i03>.

r-epiforsk 0.2.0
Propagated dependencies: r-vgam@1.1-13 r-tidyr@1.3.1 r-svyvgam@1.3 r-survival@3.8-3 r-survey@4.4-8 r-stringr@1.6.0 r-rlang@1.1.6 r-purrr@1.2.0 r-progressr@0.18.0 r-policytree@1.2.3 r-patchwork@1.3.2 r-nnet@7.3-20 r-matchit@4.7.2 r-hmisc@5.2-4 r-gridextra@2.3 r-grf@2.5.0 r-glue@1.8.0 r-ggplot2@4.0.1 r-forcats@1.0.1 r-dplyr@1.1.4 r-data-table@1.17.8 r-cowplot@1.2.0 r-broom@1.0.10
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/Laksafoss/EpiForsk
Licenses: Expat
Build system: r
Synopsis: Code Sharing at the Department of Epidemiology Research at Statens Serum Institut
Description:

This is a collection of assorted functions and examples collected from various projects. Currently we have functionalities for simplifying overlapping time intervals, Charlson comorbidity score constructors for Danish data, getting frequency for multiple variables, getting standardized output from logistic and log-linear regressions, sibling design linear regression functionalities a method for calculating the confidence intervals for functions of parameters from a GLM, Bayes equivalent for hypothesis testing with asymptotic Bayes factor, and several help functions for generalized random forest analysis using grf'.

r-ezplot 0.8.2
Propagated dependencies: r-rlang@1.1.6 r-lubridate@1.9.4 r-ggplot2@4.0.1 r-forcats@1.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/wkostelecki/ezplot
Licenses: Expat
Build system: r
Synopsis: Functions for Common Chart Types
Description:

Wrapper for the ggplot2 package that creates a variety of common charts (e.g. bar, line, area, ROC, waterfall, pie) while aiming to reduce typing.

r-extremebounds 0.1.7
Propagated dependencies: r-formula@1.2-5
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=ExtremeBounds
Licenses: GPL 2+
Build system: r
Synopsis: Extreme Bounds Analysis (EBA)
Description:

An implementation of Extreme Bounds Analysis (EBA), a global sensitivity analysis that examines the robustness of determinants in regression models. The package supports both Leamer's and Sala-i-Martin's versions of EBA, and allows users to customize all aspects of the analysis.

r-epinow2 1.8.0
Propagated dependencies: r-truncnorm@1.0-9 r-stanheaders@2.32.10 r-scales@1.4.0 r-runner@0.4.4 r-rstantools@2.5.0 r-rstan@2.32.7 r-rlang@1.1.6 r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-r-utils@2.13.0 r-purrr@1.2.0 r-primarycensored@1.3.0 r-posterior@1.6.1 r-patchwork@1.3.2 r-lubridate@1.9.4 r-lifecycle@1.0.4 r-ggplot2@4.0.1 r-futile-logger@1.4.3 r-data-table@1.17.8 r-cli@3.6.5 r-checkmate@2.3.3 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://epiforecasts.io/EpiNow2/
Licenses: Expat
Build system: r
Synopsis: Estimate and Forecast Real-Time Infection Dynamics
Description:

Estimates the time-varying reproduction number, rate of spread, and doubling time using a renewal equation approach combined with Bayesian inference via Stan. Supports Gaussian process and random walk priors for modelling changes in transmission over time. Accounts for delays between infection and observation (incubation period, reporting delays), right-truncation in recent data, day-of-week effects, and observation overdispersion. Can estimate relationships between primary and secondary outcomes (e.g., cases to hospitalisations or deaths) and forecast both. Runs across multiple regions in parallel. Based on Abbott et al. (2020) <doi:10.12688/wellcomeopenres.16006.1> and Gostic et al. (2020) <doi:10.1101/2020.06.18.20134858>.

r-easyanova 11.0
Propagated dependencies: r-nlme@3.1-168
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=easyanova
Licenses: GPL 2
Build system: r
Synopsis: Analysis of Variance and Other Important Complementary Analyses
Description:

Perform analysis of variance and other important complementary analyses. The functions are easy to use. Performs analysis in various designs, with balanced and unbalanced data.

r-esg 1.3
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=ESG
Licenses: GPL 2+
Build system: r
Synopsis: Package for Asset Projection
Description:

Presents a "Scenarios" class containing general parameters, risk parameters and projection results. Risk parameters are gathered together into a ParamsScenarios sub-object. The general process for using this package is to set all needed parameters in a Scenarios object, use the customPathsGeneration method to proceed to the projection, then use xxx_PriceDistribution() methods to get asset prices.

r-embed 1.2.2
Propagated dependencies: r-withr@3.0.2 r-vctrs@0.6.5 r-uwot@0.2.4 r-tidyr@1.3.1 r-tibble@3.3.0 r-rsample@1.3.1 r-rlang@1.1.6 r-recipes@1.3.1 r-purrr@1.2.0 r-lifecycle@1.0.4 r-glue@1.8.0 r-generics@0.1.4 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://embed.tidymodels.org
Licenses: Expat
Build system: r
Synopsis: Extra Recipes for Encoding Predictors
Description:

Predictors can be converted to one or more numeric representations using a variety of methods. Effect encodings using simple generalized linear models <doi:10.48550/arXiv.1611.09477> or nonlinear models <doi:10.48550/arXiv.1604.06737> can be used. There are also functions for dimension reduction and other approaches.

r-eyetools 0.9.2
Propagated dependencies: r-zoo@1.8-14 r-viridis@0.6.5 r-rlang@1.1.6 r-png@0.1-8 r-pbapply@1.7-4 r-magick@2.9.0 r-lifecycle@1.0.4 r-hdf5r@1.3.12 r-glue@1.8.0 r-ggplot2@4.0.1 r-ggforce@0.5.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://tombeesley.github.io/eyetools/
Licenses: GPL 3
Build system: r
Synopsis: Analyse Eye Data
Description:

Enables the automation of actions across the pipeline, including initial steps of transforming binocular data and gap repair to event-based processing such as fixations, saccades, and entry/duration in Areas of Interest (AOIs). It also offers visualisation of eye movement and AOI entries. These tools take relatively raw (trial, time, x, and y form) data and can be used to return fixations, saccades, and AOI entries and time spent in AOIs. As the tools rely on this basic data format, the functions can work with data from any eye tracking device. Implements fixation and saccade detection using methods proposed by Salvucci and Goldberg (2000) <doi:10.1145/355017.355028>.

r-exams 2.4-3
Dependencies: pandoc@2.19.2
Propagated dependencies: r-rmarkdown@2.30 r-knitr@1.50 r-base64enc@0.1-3
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: Automatic Generation of Exams in R
Description:

Automatic generation of exams based on exercises in Markdown or LaTeX format, possibly including R code for dynamic generation of exercise elements. Exercise types include single-choice and multiple-choice questions, arithmetic problems, string questions, and combinations thereof (cloze). Output formats include standalone files (PDF, HTML, Docx, ODT, ...), Moodle XML, QTI 1.2, QTI 2.1, Blackboard, Canvas, OpenOlat, ILIAS, TestVision, Particify, ARSnova, Kahoot!, Grasple, and TCExam. In addition to fully customizable PDF exams, a standardized PDF format (NOPS) is provided that can be printed, scanned, and automatically evaluated.

r-eseis 0.8.1
Propagated dependencies: r-xml@3.99-0.20 r-terra@1.8-86 r-signal@1.8-1 r-shiny@1.11.1 r-rmarkdown@2.30 r-reticulate@1.44.1 r-rcpp@1.1.0 r-minpack-lm@1.2-4 r-matrixstats@1.5.0 r-fftw@1.0-9 r-extradistr@1.10.0 r-colorspace@2.1-2 r-catools@1.18.3
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=eseis
Licenses: GPL 3
Build system: r
Synopsis: Environmental Seismology Toolbox
Description:

Environmental seismology is a scientific field that studies the seismic signals, emitted by Earth surface processes. This package provides all relevant functions to read/write seismic data files, prepare, analyse and visualise seismic data, and generate reports of the processing history.

r-enchange 1.1
Propagated dependencies: r-rcpp@1.1.0 r-iterators@1.0.14 r-hawkes@0.0-4 r-foreach@1.5.2 r-doparallel@1.0.17 r-acdm@1.1.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=eNchange
Licenses: GPL 2+
Build system: r
Synopsis: Ensemble Methods for Multiple Change-Point Detection
Description:

This package implements a segmentation algorithm for multiple change-point detection in univariate time series using the Ensemble Binary Segmentation of Korkas (2022) <Journal of the Korean Statistical Society, 51(1), pp.65-86.>.

r-era 0.5.0
Propagated dependencies: r-vctrs@0.6.5 r-rlang@1.1.6 r-pillar@1.11.1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://era.joeroe.io
Licenses: Expat
Build system: r
Synopsis: Year-Based Time Scales
Description:

This package provides a consistent representation of year-based time scales as a numeric vector with an associated era'. There are built-in era definitions for many year numbering systems used in contemporary and historic calendars (e.g. Common Era, Islamic Hijri years); year-based time scales used in archaeology, astronomy, geology, and other palaeosciences (e.g. Before Present, SI-prefixed annus'); and support for arbitrary user-defined eras. Years can converted from any one era to another using a generalised transformation function. Methods are also provided for robust casting and coercion between years and other numeric types, type-stable arithmetic with years, and pretty-printing in tables.

r-emburden 0.6.1
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-spatstat-univar@3.1-5 r-scales@1.4.0 r-rlang@1.1.6 r-readr@2.1.6 r-rappdirs@0.3.3 r-httr@1.4.7 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/ericscheier/emburden
Licenses: AGPL 3+
Build system: r
Synopsis: Energy Burden Analysis Using Net Energy Return Methodology
Description:

Calculate and analyze household energy burden using the Net Energy Return aggregation methodology. Functions support weighted statistical calculations across geographic and demographic cohorts, with utilities for formatting results into publication-ready tables. Methods are based on Scheier & Kittner (2022) <doi:10.1038/s41467-021-27673-y>.

r-eummd 0.2.0
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=eummd
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Efficient Univariate Maximum Mean Discrepancy
Description:

Computes maximum mean discrepancy two-sample test for univariate data using the Laplacian kernel, as described in Bodenham and Kawahara (2023) <doi:10.1007/s11222-023-10271-x>. The p-value is computed using permutations. Also includes implementation for computing the robust median difference statistic Q_n from Croux and Rousseeuw (1992) <doi:10.1007/978-3-662-26811-7_58> based on Johnson and Mizoguchi (1978) <doi:10.1137/0207013>.

r-efafactors 1.2.4
Propagated dependencies: r-xgboost@1.7.11.1 r-simcormultres@1.9.0 r-reticulate@1.44.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-ranger@0.17.0 r-psych@2.5.6 r-proxy@0.4-27 r-mlr@2.19.3 r-matrix@1.7-4 r-mass@7.3-65 r-ineq@0.2-13 r-ddpcr@1.16.0 r-checkmate@2.3.3 r-bbmisc@1.13
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://haijiangqin.com/EFAfactors/
Licenses: GPL 3
Build system: r
Synopsis: Determining the Number of Factors in Exploratory Factor Analysis
Description:

This package provides a collection of standard factor retention methods in Exploratory Factor Analysis (EFA), making it easier to determine the number of factors. Traditional methods such as the scree plot by Cattell (1966) <doi:10.1207/s15327906mbr0102_10>, Kaiser-Guttman Criterion (KGC) by Guttman (1954) <doi:10.1007/BF02289162> and Kaiser (1960) <doi:10.1177/001316446002000116>, and flexible Parallel Analysis (PA) by Horn (1965) <doi:10.1007/BF02289447> based on eigenvalues form PCA or EFA are readily available. This package also implements several newer methods, such as the Empirical Kaiser Criterion (EKC) by Braeken and van Assen (2017) <doi:10.1037/met0000074>, Comparison Data (CD) by Ruscio and Roche (2012) <doi:10.1037/a0025697>, and Hull method by Lorenzo-Seva et al. (2011) <doi:10.1080/00273171.2011.564527>, as well as some AI-based methods like Comparison Data Forest (CDF) by Goretzko and Ruscio (2024) <doi:10.3758/s13428-023-02122-4> and Factor Forest (FF) by Goretzko and Buhner (2020) <doi:10.1037/met0000262>. Additionally, it includes a deep neural network (DNN) trained on large-scale datasets that can efficiently and reliably determine the number of factors.

r-evalitr 1.0.0
Propagated dependencies: r-superlearner@2.0-29 r-scales@1.4.0 r-rqpen@4.2 r-rpart@4.1.24 r-rlang@1.1.6 r-quadprog@1.5-8 r-purrr@1.2.0 r-matrix@1.7-4 r-mass@7.3-65 r-haven@2.5.5 r-grf@2.5.0 r-glmnet@4.1-10 r-ggthemes@5.1.0 r-ggplot2@4.0.1 r-ggdist@3.3.3 r-gbm@2.2.2 r-forcats@1.0.1 r-e1071@1.7-16 r-dplyr@1.1.4 r-cli@3.6.5 r-caret@7.0-1 r-bartcause@1.0-10
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/MichaelLLi/evalITR
Licenses: GPL 2+
Build system: r
Synopsis: Evaluating Individualized Treatment Rules
Description:

This package provides various statistical methods for evaluating Individualized Treatment Rules under randomized data. The provided metrics include Population Average Value (PAV), Population Average Prescription Effect (PAPE), Area Under Prescription Effect Curve (AUPEC). It also provides the tools to analyze Individualized Treatment Rules under budget constraints. Detailed reference in Imai and Li (2019) <arXiv:1905.05389>.

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