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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-efred 0.1.0
Propagated dependencies: r-jsonlite@2.0.0 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=eFRED
Licenses: Expat
Build system: r
Synopsis: Fetch Data from the Federal Reserve Economic Database
Description:

Interact with the FRED API, <https://fred.stlouisfed.org/docs/api/fred/>, to fetch observations across economic series; find information about different economic sources, releases, series, etc.; conduct searches by series name, attributes, or tags; and determine the latest updates. Includes functions for creating panels of related variables with minimal effort and datasets containing data sources, releases, and popular FRED tags.

r-echogram 0.1.3
Propagated dependencies: r-readhac@1.0 r-pals@1.10 r-geosphere@1.5-20
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/hvillalo/echogram
Licenses: GPL 3
Build system: r
Synopsis: Echogram Visualisation and Analysis
Description:

Easily import multi-frequency acoustic data stored in HAC files (see <doi:10.17895/ices.pub.5482> for more information on the format), and produce echogram visualisations with predefined or customized color palettes. It is also possible to merge consecutive echograms; mask or delete unwanted echogram areas; model and subtract background noise; and more important, develop, test and interpret different combinations of frequencies in order to perform acoustic filtering of the echogram's data.

r-es 1.1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=ES
Licenses: GPL 2
Build system: r
Synopsis: Edge Selection
Description:

Implementation of the Edge Selection Algorithm for undirected graph selection. The least angle regression-based algorithm selects edges of an undirected graph based on the projection of the current residuals on the two dimensional edge-planes. The algorithm selects symmetric adjacency matrix, which many other regression-based undirected graph selection procedures cannot do.

r-extracttraindata 9.1.6
Propagated dependencies: r-raster@3.6-32
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=ExtractTrainData
Licenses: GPL 3
Build system: r
Synopsis: Extract Values from Raster
Description:

By using a multispectral image and ESRI shapefile (Point/ Line/ Polygon), a data table will be generated for classification, regression or other processing. The data table will be contained by band wise raster values and shapefile ids (User Defined).

r-eplusr 0.16.3
Propagated dependencies: r-units@1.0-0 r-stringi@1.8.7 r-rsqlite@2.4.4 r-r6@2.6.1 r-processx@3.8.6 r-lubridate@1.9.4 r-data-table@1.17.8 r-cli@3.6.5 r-checkmate@2.3.3 r-callr@3.7.6
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://hongyuanjia.github.io/eplusr/
Licenses: Expat
Build system: r
Synopsis: Toolkit for Using Whole Building Simulation Program 'EnergyPlus'
Description:

This package provides a rich toolkit of using the whole building simulation program EnergyPlus'(<https://energyplus.net>), which enables programmatic navigation, modification of EnergyPlus models and makes it less painful to do parametric simulations and analysis.

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-ess 1.1.2.1
Propagated dependencies: r-rcpp@1.1.0 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/mlindsk/ess
Licenses: GPL 3
Build system: r
Synopsis: Efficient Stepwise Selection in Decomposable Models
Description:

An implementation of the ESS algorithm following Amol Deshpande, Minos Garofalakis, Michael I Jordan (2013) <doi:10.48550/arXiv.1301.2267>. The ESS algorithm is used for model selection in decomposable graphical models.

r-ectsvr 0.1.0
Propagated dependencies: r-weightsvm@1.7-16 r-vars@1.6-1 r-urca@1.3-4
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=ECTSVR
Licenses: Expat
Build system: r
Synopsis: Cointegration Based Support Vector Regression Model
Description:

The cointegration based support vector regression model enables researchers to use data obtained from the cointegrating vector as input in the support vector regression model.

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-epanetreader 1.0.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/bradleyjeck/epanetReader
Licenses: Expat
Build system: r
Synopsis: Read Epanet Files into R
Description:

Reads water network simulation data in Epanet text-based .inp and .rpt formats into R. Also reads results from Epanet-msx'. Provides basic summary information and plots. The README file has a quick introduction. See <https://www.epa.gov/water-research/epanet> for more information on the Epanet software for modeling hydraulic and water quality behavior of water piping systems.

r-emar 1.0.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=EMAR
Licenses: GPL 3+
Build system: r
Synopsis: Empirical Model Assessment
Description:

This package provides a tool that allows users to generate various indices for evaluating statistical models. The fitstat() function computes indices based on the fitting data. The valstat() function computes indices based on the validation data set. Both fitstat() and valstat() will return 16 indices SSR: residual sum of squares, TRE: total relative error, Bias: mean bias, MRB: mean relative bias, MAB: mean absolute bias, MAPE: mean absolute percentage error, MSE: mean squared error, RMSE: root mean square error, Percent.RMSE: percentage root mean squared error, R2: coefficient of determination, R2adj: adjusted coefficient of determination, APC: Amemiya's prediction criterion, logL: Log-likelihood, AIC: Akaike information criterion, AICc: corrected Akaike information criterion, BIC: Bayesian information criterion, HQC: Hannan-Quin information criterion. The lower the better for the SSR, TRE, Bias, MRB, MAB, MAPE, MSE, RMSE, Percent.RMSE, APC, AIC, AICc, BIC and HQC indices. The higher the better for R2 and R2adj indices. Petre Stoica, P., Selén, Y. (2004) <doi:10.1109/MSP.2004.1311138>\n Zhou et al. (2023) <doi:10.3389/fpls.2023.1186250>\n Ogana, F.N., Ercanli, I. (2021) <doi:10.1007/s11676-021-01373-1>\n Musabbikhah et al. (2019) <doi:10.1088/1742-6596/1175/1/012270>.

r-exactvartest 0.1.3
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/YujianCHEN219/ExactVaRTest
Licenses: GPL 3+
Build system: r
Synopsis: Exact Finite-Sample Value-at-Risk Back-Testing
Description:

This package provides fast dynamic-programming algorithms in C++'/'Rcpp (with pure R fallbacks) for the exact finite-sample distributions and p-values of Christoffersen (1998) independence (IND) and conditional-coverage (CC) VaR backtests. For completeness, it also provides the exact unconditional-coverage (UC) test following Kupiec (1995) via a closed-form binomial enumeration. See Christoffersen (1998) <doi:10.2307/2527341> and Kupiec (1995) <doi:10.3905/jod.1995.407942>.

r-earthtones 0.2.0
Propagated dependencies: r-terra@1.8-86 r-sf@1.0-23 r-maptiles@0.11.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=earthtones
Licenses: Expat
Build system: r
Synopsis: Derive a Color Palette from a Particular Location on Earth
Description:

Downloads a satellite image via ESRI and maptiles (these are originally from a variety of aerial photography sources), translates the image into a perceptually uniform color space, runs one of a few different clustering algorithms on the colors in the image searching for a user-supplied number of colors, and returns the resulting color palette.

r-ecotolerance 0.1.0
Propagated dependencies: r-sf@1.0-23 r-raster@3.6-32 r-magrittr@2.0.4 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://cran.r-project.org/package=ecoTolerance
Licenses: GPL 3+
Build system: r
Synopsis: Ecological Tolerance Indices
Description:

Computes the Road Tolerance Index (RTI) and the Human Footprint Tolerance Index (HFTI) for species occurrence data. It automates data cleaning and integrates spatial data (roads and human footprint) to produce reproducible tolerance metrics for biodiversity and conservation research. The HFTI calculation is based on the global human footprint dataset by Mu et al. (2022) <doi:10.1038/s41597-022-01284-8>. This package is part of a PhD thesis focused on amphibian ecology in Brazil.

r-et-nwfva 0.2.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/rnuske/et.nwfva
Licenses: Expat
Build system: r
Synopsis: Forest Yield Tables for Northwest Germany and their Application
Description:

The new yield tables developed by the Northwest German Forest Research Institute (NW-FVA) provide a forest management tool for the five main commercial tree species oak, beech, spruce, Douglas-fir and pine for northwestern Germany. The new method applied for deriving yield tables combines measurements of growth and yield trials with growth simulations using a state-of-the-art single-tree growth simulator. By doing so, the new yield tables reflect the current increment level and the recommended graduated thinning from above is the underlying management concept. The yield tables are provided along with methods for deriving the site index and for interpolating between age and site indices and extrapolating beyond age and site index ranges. The inter-/extrapolations are performed traditionally by the rule of proportion or with a functional approach.

r-ecorisk 0.3.1
Propagated dependencies: r-tibble@3.3.0 r-rlang@1.1.6 r-mgcv@1.9-4 r-forecast@8.24.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/HeleneGutte/ecorisk
Licenses: Expat
Build system: r
Synopsis: Risk Assessments for Ecosystems or Ecosystem Components
Description:

Implementation of a modular framework for ecosystem risk assessments, combining existing risk assessment approaches tailored to semi-quantitative and quantitative analyses.

r-ecoval 1.2.10
Propagated dependencies: r-utility@1.4.7 r-rivernet@1.2.3 r-jpeg@0.1-11 r-fs@1.6.6
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=ecoval
Licenses: GPL 3
Build system: r
Synopsis: Procedures for Ecological Assessment of Surface Waters
Description:

This package provides functions for evaluating and visualizing ecological assessment procedures for surface waters containing physical, chemical and biological assessments in the form of value functions.

r-ezfragility 2.1.1
Propagated dependencies: r-viridis@0.6.5 r-rlang@1.1.6 r-reshape2@1.4.5 r-ramify@0.4.0 r-progress@1.2.3 r-glue@1.8.0 r-ggtext@0.1.2 r-ggplot2@4.0.1 r-foreach@1.5.2 r-epoch@1.0.7
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/Jiefei-Wang/EZFragility
Licenses: GPL 3+
Build system: r
Synopsis: Compute Neural Fragility for Ictal iEEG Time Series
Description:

This package provides tools to compute the neural fragility matrix from intracranial electrocorticographic (iEEG) recordings, enabling the analysis of brain dynamics during seizures. The package implements the method described by Li et al. (2017) <doi:10.23919/ACC.2017.7963378> and includes functions for data preprocessing ('Epoch'), fragility computation ('calcAdjFrag'), and visualization.

r-energymethod 1.1
Propagated dependencies: r-rcpparmadillo@15.2.2-1 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=energymethod
Licenses: GPL 3
Build system: r
Synopsis: Two-Sample Test of many Functional Means using the Energy Method
Description:

Given two samples of size n_1 and n_2 from a data set where each sample consists of K functional observations (channels), each recorded on T grid points, the function energy method implements a hypothesis test of equality of channel-wise mean at each channel using the bootstrapped distribution of maximum energy to control family wise error. The function energy_method_complex accomodates complex valued functional observations.

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-eix 1.2.1
Propagated dependencies: r-xgboost@1.7.11.1 r-tidyr@1.3.1 r-scales@1.4.0 r-purrr@1.2.0 r-mass@7.3-65 r-ibreakdown@2.1.2 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-ggiraphextra@0.3.0 r-data-table@1.17.8 r-dalex@2.5.3
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/ModelOriented/EIX
Licenses: GPL 2
Build system: r
Synopsis: Explain Interactions in 'XGBoost'
Description:

Structure mining from XGBoost and LightGBM models. Key functionalities of this package cover: visualisation of tree-based ensembles models, identification of interactions, measuring of variable importance, measuring of interaction importance, explanation of single prediction with break down plots (based on xgboostExplainer and iBreakDown packages). To download the LightGBM use the following link: <https://github.com/Microsoft/LightGBM>. EIX is a part of the DrWhy.AI universe.

r-ebrahim-gof 1.0.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://github.com/ebrahimkhaled/ebrahim.gof
Licenses: GPL 3
Build system: r
Synopsis: Ebrahim-Farrington Goodness-of-Fit Test for Logistic Regression
Description:

This package implements the Ebrahim-Farrington goodness-of-fit test for logistic regression models, particularly effective for sparse data and binary outcomes. This test provides an improved alternative to the traditional Hosmer-Lemeshow test by using a modified Pearson chi-square statistic with data-dependent grouping. The test is based on Farrington (1996) theoretical framework but simplified for practical implementation with binary data. Includes functions for both the original Farrington test (for grouped data) and the new Ebrahim-Farrington test (for binary data with automatic grouping). For more details see Hosmer (1980) <doi:10.1080/03610928008827941> and Farrington (1996) <doi:10.1111/j.2517-6161.1996.tb02086.x>.

r-esquisse 2.1.0
Propagated dependencies: r-zip@2.3.3 r-shinywidgets@0.9.0 r-shinybusy@0.3.3 r-shiny@1.11.1 r-scales@1.4.0 r-rstudioapi@0.17.1 r-rlang@1.1.6 r-phosphoricons@0.2.1 r-jsonlite@2.0.0 r-htmltools@0.5.8.1 r-ggplot2@4.0.1 r-downlit@0.4.5 r-datamods@1.5.3 r-bslib@0.9.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://dreamrs.github.io/esquisse/
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Explore and Visualize Your Data Interactively
Description:

This package provides a shiny gadget to create ggplot2 figures interactively with drag-and-drop to map your variables to different aesthetics. You can quickly visualize your data accordingly to their type, export in various formats, and retrieve the code to reproduce the plot.

r-epicasting 0.1.0
Propagated dependencies: r-wavelets@0.3-0.2 r-metrics@0.1.4 r-forecast@8.24.0
Channel: guix-cran
Location: guix-cran/packages/e.scm (guix-cran packages e)
Home page: https://cran.r-project.org/package=epicasting
Licenses: GPL 2+
Build system: r
Synopsis: Ewnet: An Ensemble Wavelet Neural Network for Forecasting and Epicasting
Description:

Method and tool for generating time series forecasts using an ensemble wavelet-based auto-regressive neural network architecture. This method provides additional support of exogenous variables and also generates confidence interval. This package provides EWNet model for time series forecasting based on the algorithm by Panja, et al. (2022) and Panja, et al. (2023) <arXiv:2206.10696> <doi:10.1016/j.chaos.2023.113124>.

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