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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-rarestr 1.1.1
Propagated dependencies: r-rdpack@2.6.4
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/pzhaonet/rarestR
Licenses: Expat
Build system: r
Synopsis: Rarefaction-Based Species Richness Estimator
Description:

Calculate rarefaction-based alpha- and beta-diversity. Offer parametric extrapolation to estimate the total expected species in a single community and the total expected shared species between two communities. Visualize the curve-fitting for these estimators.

r-rbf 2.1.1
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://cran.r-project.org/package=RBF
Licenses: GPL 3+
Build system: r
Synopsis: Robust Backfitting
Description:

This package provides a robust backfitting algorithm for additive models based on (robust) local polynomial kernel smoothers. It includes both bounded and re-descending (kernel) M-estimators, and it computes predictions for points outside the training set if desired. See Boente, Martinez and Salibian-Barrera (2017) <doi:10.1080/10485252.2017.1369077> and Martinez and Salibian-Barrera (2021) <doi:10.21105/joss.02992> for details.

r-rjdworkspace 1.2.0
Propagated dependencies: r-xml@3.99-0.20 r-rjdemetra@0.2.8 r-rjava@1.0-11
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/InseeFrLab/rjdworkspace
Licenses: FSDG-compatible
Build system: r
Synopsis: Manipulate 'JDemetra+' Workspaces
Description:

Set of tools to manipulate the JDemetra+ workspaces. Based on the RJDemetra package (which interfaces with version 2 of the JDemetra+ (<https://github.com/jdemetra/jdemetra-app>), the seasonal adjustment software officially recommended to the members of the European Statistical System (ESS) and the European System of Central Banks). This package provides access to additional workspace manipulation functions such as metadata manipulation, raw paths and wrangling of several workspaces simultaneously. These additional functionalities are useful as part of a CVS data production chain.

r-rumidas 0.1.3
Propagated dependencies: r-zoo@1.8-14 r-xts@0.14.1 r-tseries@0.10-58 r-roll@1.2.0 r-rdpack@2.6.4 r-maxlik@1.5-2.1 r-lubridate@1.9.4
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://cran.r-project.org/package=rumidas
Licenses: GPL 3
Build system: r
Synopsis: Univariate GARCH-MIDAS, Double-Asymmetric GARCH-MIDAS and MEM-MIDAS
Description:

Adds the MIxing-Data Sampling (MIDAS, Ghysels et al. (2007) <doi:10.1080/07474930600972467>) components to a variety of GARCH and MEM (Engle (2002) <doi:10.1002/jae.683>, Engle and Gallo (2006) <doi:10.1016/j.jeconom.2005.01.018>, and Amendola et al. (2024) <doi:10.1016/j.seps.2023.101764>) models, with the aim of predicting the volatility with additional low-frequency (that is, MIDAS) terms. The estimation takes place through simple functions, which provide in-sample and (if present) and out-of-sample evaluations. rumidas also offers a summary tool, which synthesizes the main information of the estimated model. There is also the possibility of generating one-step-ahead and multi-step-ahead forecasts.

r-r62s3 1.4.1
Propagated dependencies: r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/RaphaelS1/R62S3/
Licenses: Expat
Build system: r
Synopsis: Automatic Method Generation from R6
Description:

After defining an R6 class, R62S3 is used to automatically generate optional S3/S4 generics and methods for dispatch. Also allows piping for R6 objects.

r-rfold 0.2.0
Propagated dependencies: r-usethis@3.2.1 r-here@1.0.2 r-glue@1.8.0 r-fs@1.6.6 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/feddelegrand7/rfold
Licenses: Expat
Build system: r
Synopsis: Working with many R Folders Within an R Package
Description:

Allows developers to work with many R folders inside a package. It offers functionalities to transfer R scripts (saved outside the R folder) into the R folder while making additional checks.

r-rcppensmallen 0.3.10.0.1
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/coatless-rpkg/rcppensmallen
Licenses: GPL 2+
Build system: r
Synopsis: Header-Only C++ Mathematical Optimization Library for 'Armadillo'
Description:

Ensmallen is a templated C++ mathematical optimization library (by the MLPACK team) that provides a simple set of abstractions for writing an objective function to optimize. Provided within are various standard and cutting-edge optimizers that include full-batch gradient descent techniques, small-batch techniques, gradient-free optimizers, and constrained optimization. The RcppEnsmallen package includes the header files from the Ensmallen library and pairs the appropriate header files from armadillo through the RcppArmadillo package. Therefore, users do not need to install Ensmallen nor Armadillo to use RcppEnsmallen'. Note that Ensmallen is licensed under 3-Clause BSD, Armadillo starting from 7.800.0 is licensed under Apache License 2, RcppArmadillo (the Rcpp bindings/bridge to Armadillo') is licensed under the GNU GPL version 2 or later. Thus, RcppEnsmallen is also licensed under similar terms. Note that Ensmallen requires a compiler that supports C++14 and Armadillo 10.8.2 or later.

r-rkea 0.0-6
Dependencies: openjdk@25
Propagated dependencies: r-tm@0.7-16 r-rkeajars@5.0-4 r-rjava@1.0-11
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://cran.r-project.org/package=RKEA
Licenses: GPL 2
Build system: r
Synopsis: R/KEA Interface
Description:

An R interface to KEA (Version 5.0). KEA (for Keyphrase Extraction Algorithm) allows for extracting keyphrases from text documents. It can be either used for free indexing or for indexing with a controlled vocabulary. For more information see <http://www.nzdl.org/Kea/>.

r-rcppsmc 0.2.9
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-fkf@0.2.6
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/rcppsmc/rcppsmc
Licenses: GPL 2+
Build system: r
Synopsis: Rcpp Bindings for Sequential Monte Carlo
Description:

R access to the Sequential Monte Carlo Template Classes by Johansen <doi:10.18637/jss.v030.i06> is provided. At present, four additional examples have been added, and the first example from the JSS paper has been extended. Further integration and extensions are planned.

r-robustt2 0.1.0
Propagated dependencies: r-shiny@1.11.1 r-rrcov@1.7-7 r-matrix@1.7-4 r-mass@7.3-65 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-forcats@1.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/SergioDanielFG/robustT2
Licenses: Expat
Build system: r
Synopsis: Robust Hotelling-Type T² Control Chart Based on the Dual STATIS Approach
Description:

This package implements a robust multivariate control-chart methodology for batch-based industrial processes with multiple correlated variables using the Dual STATIS (Structuration des Tableaux A Trois Indices de la Statistique) framework. A robust compromise covariance matrix is constructed from Phase I batches with the Minimum Covariance Determinant (MCD) estimator, and a Hotelling-type T² statistic is applied for anomaly detection in Phase II. The package includes functions to simulate clean and contaminated batches, to compute both robust and classical Hotelling T² control charts, to visualize results via robust biplots, and to launch an interactive shiny dashboard. An internal dataset (pharma_data) is provided for reproducibility. See Lavit, Escoufier, Sabatier and Traissac (1994) <doi:10.1016/0167-9473(94)90134-1> for the original STATIS methodology, and Rousseeuw and Van Driessen (1999) <doi:10.1080/00401706.1999.10485670> for the MCD estimator.

r-rpca 0.2.3
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://cran.r-project.org/package=rpca
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: RobustPCA: Decompose a Matrix into Low-Rank and Sparse Components
Description:

Suppose we have a data matrix, which is the superposition of a low-rank component and a sparse component. Candes, E. J., Li, X., Ma, Y., & Wright, J. (2011). Robust principal component analysis?. Journal of the ACM (JACM), 58(3), 11. prove that we can recover each component individually under some suitable assumptions. It is possible to recover both the low-rank and the sparse components exactly by solving a very convenient convex program called Principal Component Pursuit; among all feasible decompositions, simply minimize a weighted combination of the nuclear norm and of the L1 norm. This package implements this decomposition algorithm resulting with Robust PCA approach.

r-radlibs 0.2.0
Propagated dependencies: r-stringr@1.6.0 r-lexicon@1.2.1 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://cran.r-project.org/package=radlibs
Licenses: Modified BSD
Build system: r
Synopsis: Build Your Own Madlibs!
Description:

Make your phrase or sentence into something funny! Pass a string with the keywords in, and get out a bit of humor.

r-rsurrogate 3.2
Propagated dependencies: r-survival@3.8-3 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://cran.r-project.org/package=Rsurrogate
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Robust Estimation of the Proportion of Treatment Effect Explained by Surrogate Marker Information
Description:

This package provides functions to estimate the proportion of treatment effect on the primary outcome that is explained by the treatment effect on the surrogate marker.

r-rocket 1.0.3
Propagated dependencies: r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/da-zar/ROCket
Licenses: GPL 3
Build system: r
Synopsis: Simple and Fast ROC Curves
Description:

This package provides a set of functions for receiver operating characteristic (ROC) curve estimation and area under the curve (AUC) calculation. All functions are designed to work with aggregated data; nevertheless, they can also handle raw samples. In ROCket', we distinguish two types of ROC curve representations: 1) parametric curves - the true positive rate (TPR) and the false positive rate (FPR) are functions of a parameter (the score), 2) functions - TPR is a function of FPR. There are several ROC curve estimation methods available. An introduction to the mathematical background of the implemented methods (and much more) can be found in de Zea Bermudez, Gonçalves, Oliveira & Subtil (2014) and Cai & Pepe (2004).

r-rwgraph 1.0.0
Propagated dependencies: r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://cran.r-project.org/package=RWgraph
Licenses: GPL 2+
Build system: r
Synopsis: Random Walks on Graphs Representing a Transactional Network
Description:

Random walk functions to extract new variables based on clients transactional behaviour. For more details, see Eddin et al. (2021) <arXiv:2112.07508v3> and Oliveira et al. (2021) <arXiv:2102.05373v2>.

r-readbrukerflexdata 1.9.3
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://strimmerlab.github.io/software/maldiquant/
Licenses: GPL 3+
Build system: r
Synopsis: Reads Mass Spectrometry Data in Bruker *flex Format
Description:

Reads data files acquired by Bruker Daltonics matrix-assisted laser desorption/ionization-time-of-flight mass spectrometer of the *flex series.

r-r-alpha-home 2.0.2
Propagated dependencies: r-writexl@1.5.4 r-tibble@3.3.0 r-rstudioapi@0.17.1 r-readxl@1.4.5 r-r6@2.6.1 r-r-utils@2.13.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-diffobj@0.3.6 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/R-alpha-act/R.AlphA.Home
Licenses: GPL 3
Build system: r
Synopsis: Feel at Home using R, Thanks to Shortcuts Functions Making it Simple
Description:

This package provides a collection of personal functions designed to simplify and streamline common R programming tasks. This package provides reusable tools and shortcuts for frequently used calculations and workflows.

r-rbam 1.1.2
Propagated dependencies: r-tidyr@1.3.1 r-rlang@1.1.6 r-rjson@0.2.23 r-r-utils@2.13.0 r-progress@1.2.3 r-mvtnorm@1.3-3 r-gridextra@2.3 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/BaM-tools/RBaM
Licenses: GPL 3
Build system: r
Synopsis: Bayesian Modeling: Estimate a Computer Model and Make Uncertain Predictions
Description:

An interface to the BaM (Bayesian Modeling) engine, a Fortran'-based executable aimed at estimating a model with a Bayesian approach and using it for prediction, with a particular focus on uncertainty quantification. Classes are defined for the various building blocks of BaM inference (model, data, error models, Markov Chain Monte Carlo (MCMC) samplers, predictions). The typical usage is as follows: (1) specify the model to be estimated; (2) specify the inference setting (dataset, parameters, error models...); (3) perform Bayesian-MCMC inference; (4) read, analyse and use MCMC samples; (5) perform prediction experiments. Technical details are available (in French) in Renard (2017) <https://hal.science/hal-02606929v1>. Examples of applications include Mansanarez et al. (2019) <doi:10.1029/2018WR023389>, Le Coz et al. (2021) <doi:10.1002/hyp.14169>, Perret et al. (2021) <doi:10.1029/2020WR027745>, Darienzo et al. (2021) <doi:10.1029/2020WR028607> and Perret et al. (2023) <doi:10.1061/JHEND8.HYENG-13101>.

r-recmap 1.0.20
Propagated dependencies: r-sp@2.2-0 r-rcpp@1.1.0 r-ga@3.2.4
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://cran.r-project.org/package=recmap
Licenses: GPL 3
Build system: r
Synopsis: Compute the Rectangular Statistical Cartogram
Description:

This package implements the RecMap MP2 construction heuristic <doi:10.1109/INFVIS.2004.57>. This algorithm draws maps according to a given statistical value, e.g., election results, population, or epidemiological data. The basic idea of the RecMap algorithm is that each map region, e.g., different countries, is represented by a rectangle. The area of each rectangle represents the statistical value provided as input to maintain zero cartographic error. Computationally intensive tasks are implemented in C++. The included vignette documents recmap algorithm usage.

r-rcmdr 2.9-5
Propagated dependencies: r-tcltk2@1.6.1 r-relimp@1.0-5 r-rcmdrmisc@2.10.1 r-lme4@1.1-37 r-effects@4.2-4 r-car@3.1-3 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/RCmdr-Project/rcmdr
Licenses: GPL 2+
Build system: r
Synopsis: R Commander
Description:

This package provides a platform-independent basic-statistics GUI (graphical user interface) for R, based on the tcltk package.

r-rdhs 0.8.1
Propagated dependencies: r-xml2@1.5.0 r-storr@1.2.6 r-sf@1.0-23 r-rlang@1.1.6 r-rappdirs@0.3.3 r-r6@2.6.1 r-qdapregex@0.7.10 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-iotools@0.3-5 r-httr@1.4.7 r-haven@2.5.5 r-getpass@0.2-4 r-foreign@0.8-90 r-digest@0.6.39 r-cli@3.6.5 r-brio@1.1.5
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://docs.ropensci.org/rdhs/
Licenses: Expat
Build system: r
Synopsis: API Client and Dataset Management for the Demographic and Health Survey (DHS) Data
Description:

This package provides a client for (1) querying the DHS API for survey indicators and metadata (<https://api.dhsprogram.com/#/index.html>), (2) identifying surveys and datasets for analysis, (3) downloading survey datasets from the DHS website, (4) loading datasets and associate metadata into R, and (5) extracting variables and combining datasets for pooled analysis.

r-rr2 1.1.1
Propagated dependencies: r-phyr@1.1.3 r-phylolm@2.6.5 r-nlme@3.1-168 r-matrix@1.7-4 r-lme4@1.1-37 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/arives/rr2
Licenses: GPL 3
Build system: r
Synopsis: R2s for Regression Models
Description:

Three methods to calculate R2 for models with correlated errors, including Phylogenetic GLS, Phylogenetic Logistic Regression, Linear Mixed Models (LMMs), and Generalized Linear Mixed Models (GLMMs). See details in Ives 2018 <doi:10.1093/sysbio/syy060>.

r-rblimp 1.0.0
Propagated dependencies: r-ggplot2@4.0.1 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/blimp-stats/rblimp
Licenses: GPL 3
Build system: r
Synopsis: Integration of 'Blimp' Software into R
Description:

This package provides an interface to Blimp software for Bayesian latent variable modeling, missing data analysis, and multiple imputation. The package generates Blimp syntax, executes Blimp models, and imports results back into R as structured objects with methods for visualization and analysis. Requires Blimp software (freely available at <https://www.appliedmissingdata.com/blimp>) to be installed separately.

r-rbw 0.3.2
Propagated dependencies: r-rlang@1.1.6 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/xiangzhou09/rbw
Licenses: GPL 3+
Build system: r
Synopsis: Residual Balancing Weights for Marginal Structural Models
Description:

Residual balancing is a robust method of constructing weights for marginal structural models, which can be used to estimate (a) the average treatment effect in a cross-sectional observational study, (b) controlled direct/mediator effects in causal mediation analysis, and (c) the effects of time-varying treatments in panel data (Zhou and Wodtke 2020 <doi:10.1017/pan.2020.2>). This package provides three functions, rbwPoint(), rbwMed(), and rbwPanel(), that produce residual balancing weights for estimating (a), (b), (c), respectively.

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