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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-detrender 1.0.5
Propagated dependencies: r-tkrplotr@0.1.7 r-dplr@1.7.8
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=detrendeR
Licenses: GPL 2+
Build system: r
Synopsis: Graphical User Interface (GUI) to Visualize and Analyze Dendrochronological Data
Description:

This package provides a Graphical User Interface (GUI) to import, save, detrend and perform standard tree-ring analyses. The interactive detrending allows the user to check how well the detrending curve fits each time-series and change it when needed.

r-dlbayes 0.1.0
Propagated dependencies: r-mass@7.3-65 r-laplacesdemon@16.1.6 r-glmnet@4.1-10 r-gigrvg@0.8 r-expm@1.0-0
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=dlbayes
Licenses: Expat
Build system: r
Synopsis: Use Dirichlet Laplace Prior to Solve Linear Regression Problem and Do Variable Selection
Description:

The Dirichlet Laplace shrinkage prior in Bayesian linear regression and variable selection, featuring: utility functions in implementing Dirichlet-Laplace priors such as visualization; scalability in Bayesian linear regression; penalized credible regions for variable selection.

r-dendronetwork 0.5.5
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-reshape2@1.4.5 r-rcy3@2.30.0 r-rcolorbrewer@1.1-3 r-lifecycle@1.0.4 r-igraph@2.2.1 r-foreach@1.5.2 r-dplyr@1.1.4 r-dplr@1.7.8 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/ropensci/dendroNetwork
Licenses: GPL 3+
Build system: r
Synopsis: Create Networks of Dendrochronological Series using Pairwise Similarity
Description:

Creating dendrochronological networks based on the similarity between tree-ring series or chronologies. The package includes various functions to compare tree-ring curves building upon the dplR package. The networks can be used to visualise and understand the relations between tree-ring curves. These networks are also very useful to estimate the provenance of wood as described in Visser (2021) <DOI:10.5334/jcaa.79> or wood-use within a structure/context/site as described in Visser and Vorst (2022) <DOI:10.1163/27723194-bja10014>.

r-describedf 0.2.1
Propagated dependencies: r-tseries@0.10-58 r-psych@2.5.6 r-fnonlinear@4052.83 r-e1071@1.7-16 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=DescribeDF
Licenses: GPL 3
Build system: r
Synopsis: Description of a Data Frame
Description:

Helps to describe a data frame in hand. Has been developed during PhD work of the maintainer. More information may be obtained from Garai and Paul (2023) <doi:10.1016/j.iswa.2023.200202>.

r-diceview 3.1-3
Propagated dependencies: r-scatterplot3d@0.3-44 r-r-cache@0.17.0 r-geometry@0.5.2 r-foreach@1.5.2 r-dicedesign@1.10
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/IRSN/DiceView
Licenses: GPL 3
Build system: r
Synopsis: Methods for Visualization of Computer Experiments Design and Surrogate
Description:

View 2D/3D sections, contour plots, mesh of excursion sets for computer experiments designs, surrogates or test functions.

r-declaredesign 1.1.0
Propagated dependencies: r-rlang@1.1.6 r-randomizr@1.0.0 r-generics@0.1.4 r-fabricatr@1.0.2 r-estimatr@1.0.6
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://declaredesign.org/r/declaredesign/
Licenses: Expat
Build system: r
Synopsis: Declare and Diagnose Research Designs
Description:

Researchers can characterize and learn about the properties of research designs before implementation using `DeclareDesign`. Ex ante declaration and diagnosis of designs can help researchers clarify the strengths and limitations of their designs and to improve their properties, and can help readers evaluate a research strategy prior to implementation and without access to results. It can also make it easier for designs to be shared, replicated, and critiqued.

r-divo 1.0.2
Propagated dependencies: r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=divo
Licenses: GPL 3+
Build system: r
Synopsis: Tools for Analysis of Diversity and Similarity in Biological Systems
Description:

This package provides a set of tools for empirical analysis of diversity (a number and frequency of different types in a population) and similarity (a number and frequency of shared types in two populations) in biological or ecological systems.

r-dpcid 1.1
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://sites.google.com/site/dhyeonyu/software
Licenses: GPL 2+
Build system: r
Synopsis: Differential Partial Correlation IDentification
Description:

Differential partial correlation identification with the ridge and the fusion penalties.

r-datamojo 1.0.0
Propagated dependencies: r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=dataMojo
Licenses: Expat
Build system: r
Synopsis: Reshape Data Table
Description:

This package provides a grammar of data manipulation with data.table', providing a consistent a series of utility functions that help you solve the most common data manipulation challenges.

r-dipw 0.1.0
Propagated dependencies: r-rmosek@1.3.5 r-matrix@1.7-4 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=dipw
Licenses: GPL 3
Build system: r
Synopsis: Debiased Inverse Propensity Score Weighting
Description:

Estimation of the average treatment effect when controlling for high-dimensional confounders using debiased inverse propensity score weighting (DIPW). DIPW relies on the propensity score following a sparse logistic regression model, but the regression curves are not required to be estimable. Despite this, our package also allows the users to estimate the regression curves and take the estimated curves as input to our methods. Details of the methodology can be found in Yuhao Wang and Rajen D. Shah (2020) "Debiased Inverse Propensity Score Weighting for Estimation of Average Treatment Effects with High-Dimensional Confounders" <arXiv:2011.08661>. The package relies on the optimisation software MOSEK <https://www.mosek.com/> which must be installed separately; see the documentation for Rmosek'.

r-datamedios 1.2.2
Propagated dependencies: r-xml2@1.5.0 r-wordcloud2@0.2.1 r-tidytext@0.4.3 r-stringr@1.6.0 r-rvest@1.0.5 r-rlang@1.1.6 r-purrr@1.2.0 r-plotly@4.11.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-ggplot2@4.0.1 r-dt@0.34.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=datamedios
Licenses: Expat
Build system: r
Synopsis: Scraping Chilean Media
Description:

This package provides a system for extracting news from Chilean media, specifically through Web Scapping from Chilean media. The package allows for news searches using search phrases and date filters, and returns the results in a structured format, ready for analysis. Additionally, it includes functions to clean the extracted data, visualize it, and store it in databases. All of this can be done automatically, facilitating the collection and analysis of relevant information from Chilean media.

r-dabestr 2025.3.15
Propagated dependencies: r-viridislite@0.4.2 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-scales@1.4.0 r-rlang@1.1.6 r-rcolorbrewer@1.1-3 r-magrittr@2.0.4 r-ggsci@4.1.0 r-ggplot2@4.0.1 r-ggbeeswarm@0.7.2 r-effsize@0.8.1 r-dplyr@1.1.4 r-cowplot@1.2.0 r-cli@3.6.5 r-brunnermunzel@2.0 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/ACCLAB/dabestr
Licenses: FSDG-compatible
Build system: r
Synopsis: Data Analysis using Bootstrap-Coupled Estimation
Description:

Data Analysis using Bootstrap-Coupled ESTimation. Estimation statistics is a simple framework that avoids the pitfalls of significance testing. It uses familiar statistical concepts: means, mean differences, and error bars. More importantly, it focuses on the effect size of one's experiment/intervention, as opposed to a false dichotomy engendered by P values. An estimation plot has two key features: 1. It presents all datapoints as a swarmplot, which orders each point to display the underlying distribution. 2. It presents the effect size as a bootstrap 95% confidence interval on a separate but aligned axes. Estimation plots are introduced in Ho et al., Nature Methods 2019, 1548-7105. <doi:10.1038/s41592-019-0470-3>. The free-to-view PDF is located at <https://www.nature.com/articles/s41592-019-0470-3.epdf?author_access_token=Euy6APITxsYA3huBKOFBvNRgN0jAjWel9jnR3ZoTv0Pr6zJiJ3AA5aH4989gOJS_dajtNr1Wt17D0fh-t4GFcvqwMYN03qb8C33na_UrCUcGrt-Z0J9aPL6TPSbOxIC-pbHWKUDo2XsUOr3hQmlRew%3D%3D>.

r-dropr 1.0.6
Propagated dependencies: r-survival@3.8-3 r-shiny@1.11.1 r-lifecycle@1.0.4 r-ggplot2@4.0.1 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://iscience-kn.github.io/dropR/
Licenses: GPL 3+
Build system: r
Synopsis: Dropout Analysis by Condition
Description:

Analysis and visualization of dropout between conditions in surveys and (online) experiments. Features include computation of dropout statistics, comparing dropout between conditions (e.g. Chi squared), analyzing survival (e.g. Kaplan-Meier estimation), comparing conditions with the most different rates of dropout (Kolmogorov-Smirnov) and visualizing the result of each in designated plotting functions. Article published in _Behavior Research Methods_ on dropR by the authors: Dropout analysis: A method for data from Internet-based research and dropR', an R-based web app and package to analyze and visualize dropout. (2025) <doi:10.3758/s13428-025-02730-2>. Sources: Andrea Frick, Marie-Terese Baechtiger & Ulf-Dietrich Reips (2001) <doi:10.5167/uzh-19758>; Ulf-Dietrich Reips (2002) <doi:10.1026//1618-3169.49.4.243>.

r-dbplot 0.3.3
Propagated dependencies: r-rlang@1.1.6 r-purrr@1.2.0 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/edgararuiz/dbplot
Licenses: GPL 3
Build system: r
Synopsis: Simplifies Plotting Data Inside Databases
Description:

Leverages dplyr to process the calculations of a plot inside a database. This package provides helper functions that abstract the work at three levels: outputs a ggplot', outputs the calculations, outputs the formula needed to calculate bins.

r-decorater 0.1.2
Propagated dependencies: r-rwekajars@3.9.3-2 r-rweka@0.4-47 r-rjava@1.0-11
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=DecorateR
Licenses: GPL 2+
Build system: r
Synopsis: Fit and Deploy DECORATE Trees
Description:

DECORATE (Diverse Ensemble Creation by Oppositional Relabeling of Artificial Training Examples) builds an ensemble of J48 trees by recursively adding artificial samples of the training data ("Melville, P., & Mooney, R. J. (2005) <DOI:10.1016/j.inffus.2004.04.001>").

r-datacutr 0.2.4
Propagated dependencies: r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-reactable@0.4.5 r-purrr@1.2.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-dplyr@1.1.4 r-assertthat@0.2.1 r-admiraldev@1.4.0
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://pharmaverse.github.io/datacutr/
Licenses: FSDG-compatible
Build system: r
Synopsis: SDTM Datacut
Description:

Supports the process of applying a cut to Standard Data Tabulation Model (SDTM), as part of the analysis of specific points in time of the data, normally as part of investigation into clinical trials. The functions support different approaches of cutting to the different domains of SDTM normally observed.

r-dwdradar 0.2.10
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=dwdradar
Licenses: GPL 2+
Build system: r
Synopsis: Read Binary Radar Files from 'DWD' (German Weather Service)
Description:

The DWD provides gridded radar data for Germany in binary format. dwdradar reads these files and enables a fast conversion into numerical format.

r-drawr 1.0.3
Propagated dependencies: r-rocr@1.0-11 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=DRaWR
Licenses: GPL 2
Build system: r
Synopsis: Discriminative Random Walk with Restart
Description:

We present DRaWR, a network-based method for ranking genes or properties related to a given gene set. Such related genes or properties are identified from among the nodes of a large, heterogeneous network of biological information. Our method involves a random walk with restarts, performed on an initial network with multiple node and edge types, preserving more of the original, specific property information than current methods that operate on homogeneous networks. In this first stage of our algorithm, we find the properties that are the most relevant to the given gene set and extract a subnetwork of the original network, comprising only the relevant properties. We then rerank genes by their similarity to the given gene set, based on a second random walk with restarts, performed on the above subnetwork.

r-damagedetective 1.0.0
Propagated dependencies: r-withr@3.0.2 r-tidyr@1.3.1 r-scales@1.4.0 r-rlang@1.1.6 r-rcpphnsw@0.6.0 r-patchwork@1.3.2 r-matrix@1.7-4 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-cowplot@1.2.0
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://alicenjoyhenning.github.io/DamageDetective/
Licenses: AGPL 3+
Build system: r
Synopsis: Detecting Damaged Cells in Single-Cell RNA Sequencing Data
Description:

Detects and filters damaged cells in single-cell RNA sequencing (scRNA-seq) data using a novel approach inspired by DoubletFinder'. Damage is detected by measuring the extent to which cells deviate from artificially damaged profiles of themselves, simulated through the probabilistic escape of cytoplasmic RNA. As output, a damage score ranging from 0 to 1 is given for each cell providing an intuitive scale for filtering that is standardised across cell types, samples, and experiments.

r-dlpca 0.0.5
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=DLPCA
Licenses: Expat
Build system: r
Synopsis: The Distributed Local PCA Algorithm
Description:

Algorithm to handle with optimal subset selection for distributed local principal component analysis. The philosophy of the package is described in Guo G. (2020) <doi:10.1080/02331888.2020.1823979>.

r-dslice 1.2.2
Propagated dependencies: r-scales@1.4.0 r-rcpp@1.1.0 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=dslice
Licenses: GPL 2+
Build system: r
Synopsis: Dynamic Slicing
Description:

Dynamic slicing is a method designed for dependency detection between a categorical variable and a continuous variable. It could be applied for non-parametric hypothesis testing and gene set enrichment analysis.

r-donutsk 0.1.1
Propagated dependencies: r-rlang@1.1.6 r-glue@1.8.0 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/dkibalnikov/donutsk
Licenses: Expat
Build system: r
Synopsis: Construct Advanced Donut Charts
Description:

Build donut/pie charts with ggplot2 layer by layer, exploiting the advantages of polar symmetry. Leverage layouts to distribute labels effectively. Connect labels to donut segments using pins. Streamline annotation and highlighting.

r-dsos 0.1.2
Propagated dependencies: r-simctest@2.6.1 r-scales@1.4.0 r-ggplot2@4.0.1 r-future-apply@1.20.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/vathymut/dsos
Licenses: GPL 3+
Build system: r
Synopsis: Dataset Shift with Outlier Scores
Description:

Test for no adverse shift in two-sample comparison when we have a training set, the reference distribution, and a test set. The approach is flexible and relies on a robust and powerful test statistic, the weighted AUC. Technical details are in Kamulete, V. M. (2021) <arXiv:1908.04000>. Modern notions of outlyingness such as trust scores and prediction uncertainty can be used as the underlying scores for example.

r-dtbm 3.0
Propagated dependencies: r-weightedcluster@2.0 r-envstats@3.1.0
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=dTBM
Licenses: GPL 2+
Build system: r
Synopsis: Multi-Way Spherical Clustering via Degree-Corrected Tensor Block Models
Description:

Implement weighted higher-order initialization and angle-based iteration for multi-way spherical clustering under degree-corrected tensor block model. See reference Jiaxin Hu and Miaoyan Wang (2023) <doi:10.1109/TIT.2023.3239521>.

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