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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-dtaxg 0.1.0
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=DTAXG
Licenses: GPL 3
Build system: r
Synopsis: Diagnostic Test Assessment in the Absence of Gold Standard
Description:

To calculate the sensitivity and specificity in the absence of gold standard using the Bayesian method. The Bayesian method can be referenced at Haiyan Gu and Qiguang Chen (1999) <doi:10.3969/j.issn.1002-3674.1999.04.004>.

r-dataqualitydashboard 2.8.6
Propagated dependencies: r-tidyselect@1.2.1 r-stringr@1.6.0 r-sqlrender@1.19.4 r-rlang@1.1.6 r-rjava@1.0-11 r-readr@2.1.6 r-plyr@1.8.9 r-parallellogger@3.5.1 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-dplyr@1.1.4 r-databaseconnector@7.1.0
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/OHDSI/DataQualityDashboard
Licenses: ASL 2.0
Build system: r
Synopsis: Execute and View Data Quality Checks on OMOP CDM Database
Description:

Assesses data quality in Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) databases. Executes data quality checks and provides an R `shiny` application to view the results.

r-depcensoring 0.1.8
Propagated dependencies: r-survival@3.8-3 r-splines2@0.5.4 r-rvinecopulib@0.7.3.1.0 r-rafalib@1.0.4 r-r6@2.6.1 r-pbivnorm@0.6.0 r-numderiv@2016.8-1.1 r-nloptr@2.2.1 r-nleqslv@3.3.5 r-mvtnorm@1.3-3 r-matrixcalc@1.0-6 r-matrix@1.7-4 r-mass@7.3-65 r-lubridate@1.9.4 r-foreach@1.5.2 r-envstats@3.1.0 r-doparallel@1.0.17 r-copula@1.1-7
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=depCensoring
Licenses: GPL 3
Build system: r
Synopsis: Statistical Methods for Survival Data with Dependent Censoring
Description:

Several statistical methods for analyzing survival data under various forms of dependent censoring are implemented in the package. In addition to accounting for dependent censoring, it offers tools to adjust for unmeasured confounding factors. The implemented approaches allow users to estimate the dependency between survival time and dependent censoring time, based solely on observed survival data. For more details on the methods, refer to Deresa and Van Keilegom (2021) <doi:10.1093/biomet/asaa095>, Czado and Van Keilegom (2023) <doi:10.1093/biomet/asac067>, Crommen et al. (2024) <doi:10.1007/s11749-023-00903-9>, Deresa and Van Keilegom (2024) <doi:10.1080/01621459.2022.2161387>, Willems et al. (2025) <doi:10.48550/arXiv.2403.11860>, Ding and Van Keilegom (2025) and D'Haen et al. (2025) <doi:10.1007/s10985-025-09647-0>.

r-dclone 2.3-3
Propagated dependencies: r-rstan@2.32.7 r-rjags@4-17 r-r2openbugs@3.2-5 r-matrix@1.7-4 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://groups.google.com/forum/#!forum/dclone-users
Licenses: GPL 2
Build system: r
Synopsis: Data Cloning and MCMC Tools for Maximum Likelihood Methods
Description:

Low level functions for implementing maximum likelihood estimating procedures for complex models using data cloning and Bayesian Markov chain Monte Carlo methods as described in Solymos 2010 <doi:10.32614/RJ-2010-011>. Sequential and parallel MCMC support for JAGS', WinBUGS', OpenBUGS', and Stan'.

r-datapackage 0.2.3
Propagated dependencies: r-yaml@2.3.10 r-jsonlite@2.0.0 r-iso8601@0.1.2
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/djvanderlaan/datapackage
Licenses: GPL 3
Build system: r
Synopsis: Creating and Reading Data Packages
Description:

Open, read data from and modify Data Packages. Data Packages are an open standard for bundling and describing data sets (<https://datapackage.org>). When data is read from a Data Package care is taken to convert the data as much a possible to R appropriate data types. The package can be extended with plugins for additional data types.

r-dosedesignr 0.3.0
Propagated dependencies: r-stringr@1.6.0 r-shinywidgets@0.9.0 r-shinyjs@2.1.0 r-shinybs@0.61.1 r-shiny@1.11.1 r-rsolnp@2.0.1 r-readxl@1.4.5 r-purrr@1.2.0 r-latticeextra@0.6-31 r-knitr@1.50 r-kableextra@1.4.0 r-ggplot2@4.0.1 r-dt@0.34.0 r-dosefinding@1.4-1
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=dosedesignR
Licenses: GPL 3
Build system: r
Synopsis: Interactive Designing of Dose Finding Studies
Description:

This package provides the user with an interactive application which can be used to facilitate the planning of dose finding studies by applying the theory of optimal experimental design.

r-dtmapi 0.1.0
Propagated dependencies: r-testthat@3.3.0 r-httr2@1.2.1 r-askpass@1.2.1
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/Displacement-Tracking-Matrix/dtmapi-R
Licenses: Expat
Build system: r
Synopsis: Fetching Data from the 'Displacement Tracking Matrix'
Description:

Allows humanitarian community, academia, media, government, and non-governmental organizations to utilize the data collected by the Displacement Tracking Matrix (<https://dtm.iom.int>), a unit in the International Organization for Migration. This also provides non-sensitive Internally Displaced Person figures, aggregated at the country, Admin 1 (states, provinces, or equivalent), and Admin 2 (smaller administrative areas) levels.

r-diagis 0.2.3
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-gridextra@2.3 r-ggplot2@4.0.1 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/helske/diagis/
Licenses: GPL 2+
Build system: r
Synopsis: Diagnostic Plot and Multivariate Summary Statistics of Weighted Samples from Importance Sampling
Description:

Fast functions for effective sample size, weighted multivariate mean, variance, and quantile computation, and weight diagnostic plot for generic importance sampling type or other probability weighted samples.

r-dhbins 1.1
Propagated dependencies: 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=DHBins
Licenses: GPL 3
Build system: r
Synopsis: Hexmaps for NZ District Health Boards
Description:

Draws stylized choropleth maps -- hexagonal maps and triangular multiclass hex maps -- for New Zealand District Health Boards and Regional Council areas. These allow faceted, coloured displays of quantitative information for comparison across District Health Boards or Regional Councils. The preprint Lumley (2019) <arXiv:1912.04435> is based on the methods in this package.

r-dynarankr 1.1.0
Propagated dependencies: r-rlang@1.1.6 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/straussed/DynaRankR
Licenses: GPL 2
Build system: r
Synopsis: Inferring Longitudinal Dominance Hierarchies
Description:

This package provides functions for inferring longitudinal dominance hierarchies, which describe dominance relationships and their dynamics in a single latent hierarchy over time. Strauss & Holekamp (in press).

r-dhsage 0.1.0
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=dhsage
Licenses: GPL 2+
Build system: r
Synopsis: Reproductive Age Female Data of Various Demographic Health Surveys
Description:

We provide 70 data sets of females of reproductive age from 19 Asian countries, ranging in age from 15 to 49. The data sets are extracted from demographic and health surveys that were conducted over an extended period of time. Moreover, the functions also provide Whippleâ s index as well as age reporting quality such as very rough, rough, approximate, accurate, and highly accurate.

r-datapackager 0.16.2
Propagated dependencies: r-yaml@2.3.10 r-usethis@3.2.1 r-rprojroot@2.1.1 r-roxygen2@7.3.3 r-rmarkdown@2.30 r-pkgload@1.4.1 r-pkgbuild@1.4.8 r-knitr@1.50 r-digest@0.6.39 r-desc@1.4.3 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/ropensci/DataPackageR
Licenses: Expat
Build system: r
Synopsis: Construct Reproducible Analytic Data Sets as R Packages
Description:

This package provides a framework to help construct R data packages in a reproducible manner. Potentially time consuming processing of raw data sets into analysis ready data sets is done in a reproducible manner and decoupled from the usual R CMD build process so that data sets can be processed into R objects in the data package and the data package can then be shared, built, and installed by others without the need to repeat computationally costly data processing. The package maintains data provenance by turning the data processing scripts into package vignettes, as well as enforcing documentation and version checking of included data objects. Data packages can be version controlled on GitHub', and used to share data for manuscripts, collaboration and reproducible research.

r-dti 1.5.4.3
Dependencies: gsl@2.8
Propagated dependencies: r-rgl@1.3.31 r-quadprog@1.5-8 r-oro-nifti@0.11.4 r-oro-dicom@0.5.3 r-gsl@2.1-9 r-awsmethods@1.1-1 r-aws@2.5-6 r-adimpro@0.9.7.2
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://www.wias-berlin.de/research/ats/imaging/
Licenses: GPL 2+
Build system: r
Synopsis: Analysis of Diffusion Weighted Imaging (DWI) Data
Description:

Diffusion Weighted Imaging (DWI) is a Magnetic Resonance Imaging modality, that measures diffusion of water in tissues like the human brain. The package contains R-functions to process diffusion-weighted data. The functionality includes diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), modeling for high angular resolution diffusion weighted imaging (HARDI) using Q-ball-reconstruction and tensor mixture models, several methods for structural adaptive smoothing including POAS and msPOAS, and a streamline fiber tracking for tensor and tensor mixture models. The package provides functionality to manipulate and visualize results in 2D and 3D.

r-drsurvcrt 0.0.1
Propagated dependencies: r-survival@3.8-3 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-pracma@2.4.6 r-ggplot2@4.0.1 r-frailtyem@1.0.1 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=DRsurvCRT
Licenses: Expat
Build system: r
Synopsis: Doubly-Robust Estimation for Survival Outcomes in Cluster-Randomized Trials
Description:

Cluster-randomized trials (CRTs) assign treatment to groups rather than individuals, so valid analyses must distinguish cluster-level and individual-level effects and define estimands within a potential-outcomes framework. This package supports right-censored survival outcomes for both single-state (binary) and multi-state settings. For single-state outcomes, it provides estimands based on stage-specific survival contrasts (SPCE) and restricted mean survival time (RMST). For multi-state outcomes, it provides SPCE as well as a generalized win-based restricted mean time-in-favor estimand (RMT-IF). The package implements doubly robust estimators that accommodate covariate-dependent censoring and remain consistent if either the outcome model or the censoring model is correctly specified. Users can choose marginal Cox or gamma-frailty Cox working models for nuisance estimation, and inference is supported via leave-one-cluster-out jackknife variance and confidence interval estimation. Methods are described in Fang et al. (2025) "Estimands and doubly robust estimation for cluster-randomized trials with survival outcomes" <doi:10.48550/arXiv.2510.08438>.

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-dwls 0.1.0
Propagated dependencies: r-varhandle@2.0.6 r-summarizedexperiment@1.40.0 r-seurat@5.3.1 r-rocr@1.0-11 r-reshape@0.8.10 r-quadprog@1.5-8 r-mast@1.36.0 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://github.com/sistia01/DWLS
Licenses: GPL 2
Build system: r
Synopsis: Gene Expression Deconvolution Using Dampened Weighted Least Squares
Description:

The rapid development of single-cell transcriptomic technologies has helped uncover the cellular heterogeneity within cell populations. However, bulk RNA-seq continues to be the main workhorse for quantifying gene expression levels due to technical simplicity and low cost. To most effectively extract information from bulk data given the new knowledge gained from single-cell methods, we have developed a novel algorithm to estimate the cell-type composition of bulk data from a single-cell RNA-seq-derived cell-type signature. Comparison with existing methods using various real RNA-seq data sets indicates that our new approach is more accurate and comprehensive than previous methods, especially for the estimation of rare cell types. More importantly,our method can detect cell-type composition changes in response to external perturbations, thereby providing a valuable, cost-effective method for dissecting the cell-type-specific effects of drug treatments or condition changes. As such, our method is applicable to a wide range of biological and clinical investigations. Dampened weighted least squares ('DWLS') is an estimation method for gene expression deconvolution, in which the cell-type composition of a bulk RNA-seq data set is computationally inferred. This method corrects common biases towards cell types that are characterized by highly expressed genes and/or are highly prevalent, to provide accurate detection across diverse cell types. See: <https://www.nature.com/articles/s41467-019-10802-z.pdf> for more information about the development of DWLS and the methods behind our functions.

r-datasda 0.1.8
Propagated dependencies: r-tidyr@1.3.1 r-rsda@3.2.5 r-magrittr@2.0.4 r-histdawass@1.0.8 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=dataSDA
Licenses: GPL 2+
Build system: r
Synopsis: Datasets and Basic Statistics for Symbolic Data Analysis
Description:

Collects a diverse range of symbolic data and offers a comprehensive set of functions that facilitate the conversion of traditional data into the symbolic data format.

r-dymep 0.1.2
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=DyMEP
Licenses: LGPL 3+
Build system: r
Synopsis: Dynamic Multi Environment Phenology-Model
Description:

Mechanistically models/predicts the phenology (macro-phases) of 10 crop plants (trained on a big dataset over 80 years derived from the German weather service (DWD) <https://opendata.dwd.de/>). Can be applied for remote sensing purposes, dynamically check the best subset of available covariates for the given dataset and crop.

r-double-truncation 1.8
Propagated dependencies: r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=double.truncation
Licenses: GPL 2
Build system: r
Synopsis: Analysis of Doubly-Truncated Data
Description:

Likelihood-based inference methods with doubly-truncated data are developed under various models. Nonparametric models are based on Efron and Petrosian (1999) <doi:10.1080/01621459.1999.10474187> and Emura, Konno, and Michimae (2015) <doi:10.1007/s10985-014-9297-5>. Parametric models from the special exponential family (SEF) are based on Hu and Emura (2015) <doi:10.1007/s00180-015-0564-z> and Emura, Hu and Konno (2017) <doi:10.1007/s00362-015-0730-y>. The parametric location-scale models are based on Dorre et al. (2021) <doi:10.1007/s00180-020-01027-6>.

r-deform 1.0.1
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=deform
Licenses: GPL 3
Build system: r
Synopsis: Spatial Deformation and Dimension Expansion Gaussian Processes
Description:

This package provides methods for fitting nonstationary Gaussian process models by spatial deformation, as introduced by Sampson and Guttorp (1992) <doi:10.1080/01621459.1992.10475181>, and by dimension expansion, as introduced by Bornn et al. (2012) <doi:10.1080/01621459.2011.646919>. Low-rank thin-plate regression splines, as developed in Wood, S.N. (2003) <doi:10.1111/1467-9868.00374>, are used to either transform co-ordinates or create new latent dimensions.

r-droptest 0.1.3
Propagated dependencies: r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/chadr/droptest
Licenses: Expat
Build system: r
Synopsis: Simulates LOX Drop Testing
Description:

Generates simulated data representing the LOX drop testing process (also known as impact testing). A simulated process allows for accelerated study of test behavior. Functions are provided to simulate trials, test series, and groups of test series. Functions for creating plots specific to this process are also included. Test attributes and criteria can be set arbitrarily. This work is not endorsed by or affiliated with NASA. See "ASTM G86-17, Standard Test Method for Determining Ignition Sensitivity of Materials to Mechanical Impact in Ambient Liquid Oxygen and Pressurized Liquid and Gaseous Oxygen Environments" <doi:10.1520/G0086-17>.

r-docket 1.33
Propagated dependencies: r-zip@2.3.3 r-xml2@1.5.0 r-xml@3.99-0.20 r-stringr@1.6.0
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://github.com/JonathanConrad98/docket
Licenses: Expat
Build system: r
Synopsis: Insert R Data into 'Word' Documents
Description:

Populate data from an R environment into .doc and .docx templates. Create a template document in a program such as Word', and add strings encased in guillemet characters to create flags («example»). Use getDictionary() to create a dictionary of flags and replacement values, then call docket() to generate a populated document.

r-dnafractal 0.0.2
Propagated dependencies: r-stringr@1.6.0 r-desctools@0.99.60
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://cran.r-project.org/package=dnafractal
Licenses: GPL 3+
Build system: r
Synopsis: Generates a Fractal Image of a DNA Sequence
Description:

The function takes a DNA sequence, a start point, an end point in the sequence, dot size and dot color and draws a fractal image of the sequence. The fractal starts in the center of the canvas. The image is drawn by moving base by base along the sequence and dropping a midpoint between the actual point and the corner designated by the actual base. For more details see Jeffrey (1990) <doi:10.1093/nar/18.8.2163>, Hill, Schisler, and Singh (1992) <doi:10.1007/BF00178602>, and Löchel and Heider (2021) <doi:10.1016/j.csbj.2021.11.008>.

r-dtrackr 0.5.0
Propagated dependencies: r-v8@8.0.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-scales@1.4.0 r-rsvg@2.7.0 r-rlang@1.1.6 r-purrr@1.2.0 r-png@0.1-8 r-pdftools@3.6.0 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-htmltools@0.5.8.1 r-glue@1.8.0 r-fs@1.6.6 r-dplyr@1.1.4 r-base64enc@0.1-3
Channel: guix-cran
Location: guix-cran/packages/d.scm (guix-cran packages d)
Home page: https://terminological.github.io/dtrackr/index.html
Licenses: Expat
Build system: r
Synopsis: Track your Data Pipelines
Description:

Track and document dplyr data pipelines. As you filter, mutate, and join your way through a data set, dtrackr seamlessly keeps track of your data flow and makes publication ready documentation of a data pipeline simple.

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