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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 search send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.


r-jrich 0.60-35
Propagated dependencies: r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://github.com/Dmirandae/jrich
Licenses: GPL 3
Build system: r
Synopsis: Jack-Knife Support for Evolutionary Distinctiveness Indices I and W
Description:

These functions calculate the taxonomic measures presented in Miranda-Esquivel (2016). The package introduces Jack-knife resampling in evolutionary distinctiveness prioritization analysis, as a way to evaluate the support of the ranking in area prioritization, and the persistence of a given area in a conservation analysis. The algorithm is described in: Miranda-Esquivel, D (2016) <DOI:10.1007/978-3-319-22461-9_11>.

r-juliaconnector 1.1.5
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=JuliaConnectoR
Licenses: FSDG-compatible
Build system: r
Synopsis: Functionally Oriented Interface for Integrating 'Julia' with R
Description:

Allows to import functions and whole packages from Julia in R. Imported Julia functions can directly be called as R functions. Data structures can be translated between Julia and R. More details can also be found in the corresponding article <doi:10.18637/jss.v101.i06>.

r-jsonld 2.2.1
Propagated dependencies: r-v8@8.0.1 r-jsonlite@2.0.0 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://docs.ropensci.org/jsonld/
Licenses: Modified BSD
Build system: r
Synopsis: JSON for Linking Data
Description:

JSON-LD <https://www.w3.org/TR/json-ld/> is a light-weight syntax for expressing linked data. It is primarily intended for web-based programming environments, interoperable web services and for storing linked data in JSON-based databases. This package provides bindings to the JavaScript library for converting, expanding and compacting JSON-LD documents.

r-journalabbr 0.4.3
Propagated dependencies: r-tidytable@0.11.2 r-stringr@1.6.0 r-stringi@1.8.7 r-shiny@1.11.1 r-purrr@1.2.0 r-httr@1.4.7 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://github.com/zoushucai/journalabbr
Licenses: GPL 3+
Build system: r
Synopsis: Journal Abbreviations for BibTeX Documents
Description:

Since the reference management software (such as Zotero', Mendeley') exports Bib file journal abbreviation is not detailed enough, the journalabbr package only abbreviates the journal field of Bib file, and then outputs a new Bib file for generating reference format with journal abbreviation on other software (such as texstudio'). The abbreviation table is from JabRef'. At the same time, Shiny application is provided to generate thebibliography', a reference format that can be directly used for latex paper writing based on Rmd files.

r-jshintr 0.1.0
Propagated dependencies: r-rstudioapi@0.17.1 r-htmlwidgets@1.6.4 r-htmltools@0.5.8.1
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://github.com/stla/jshintr
Licenses: GPL 3
Build system: r
Synopsis: Lint 'JavaScript' Files
Description:

Allow to run jshint on JavaScript files with a R command or a RStudio addin. The report appears in the RStudio viewer pane.

r-jsm 1.0.2
Propagated dependencies: r-survival@3.8-3 r-statmod@1.5.1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-nlme@3.1-168
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=JSM
Licenses: Modified BSD
Build system: r
Synopsis: Semiparametric Joint Modeling of Survival and Longitudinal Data
Description:

Maximum likelihood estimation for the semiparametric joint modeling of survival and longitudinal data. Refer to the Journal of Statistical Software article: <doi:10.18637/jss.v093.i02>.

r-jsmediation 0.2.3
Propagated dependencies: r-tidyselect@1.2.1 r-tibble@3.3.0 r-rlang@1.1.6 r-purrr@1.2.0 r-mass@7.3-65 r-magrittr@2.0.4 r-knitr@1.50 r-glue@1.8.0 r-dplyr@1.1.4 r-data-table@1.17.8 r-broom@1.0.10
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://jsmediation.cedricbatailler.me/
Licenses: Expat
Build system: r
Synopsis: Mediation Analysis Using Joint Significance
Description:

This package provides a set of helper functions to conduct joint-significance tests for mediation analysis, as recommended by Yzerbyt, Muller, Batailler, & Judd. (2018) <doi:10.1037/pspa0000132>.

r-jmi 0.1.0
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=JMI
Licenses: GPL 2+
Build system: r
Synopsis: Jackknife Mutual Information
Description:

Computes the Jackknife Mutual Information (JMI) between two random vectors and provides the p-value for dependence tests. See Zeng, X., Xia, Y. and Tong, H. (2018) <doi:10.1073/pnas.1715593115>.

r-jfa 0.7.4
Propagated dependencies: r-truncdist@1.0-2 r-stanheaders@2.32.10 r-rstantools@2.5.0 r-rstan@2.32.7 r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-ggplot2@4.0.1 r-extradistr@1.10.0 r-bh@1.87.0-1 r-bde@1.0.1.1
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://koenderks.github.io/jfa/
Licenses: GPL 3+
Build system: r
Synopsis: Statistical Methods for Auditing
Description:

This package provides statistical methods for auditing as implemented in JASP for Audit (Derks et al., 2021 <doi:10.21105/joss.02733>). First, the package makes it easy for an auditor to plan a statistical sample, select the sample from the population, and evaluate the misstatement in the sample compliant with international auditing standards. Second, the package provides statistical methods for auditing data, including tests of digit distributions and repeated values. Finally, the package includes methods for auditing algorithms on the aspect of fairness and bias. Next to classical statistical methodology, the package implements Bayesian equivalents of these methods whose statistical underpinnings are described in Derks et al. (2021) <doi:10.1111/ijau.12240>, Derks et al. (2024) <doi:10.2308/AJPT-2021-086>, Derks et al. (2022) <doi:10.31234/osf.io/8nf3e> Derks et al. (2024) <doi:10.31234/osf.io/tgq5z>, and Derks et al. (2025) <doi:10.31234/osf.io/b8tu2>.

r-jds-rmd 0.3.4
Propagated dependencies: r-rmarkdown@2.30 r-bookdown@0.45
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://github.com/wenjie2wang/jds.rmd
Licenses: GPL 3+
Build system: r
Synopsis: R Markdown Templates for Journal of Data Science
Description:

Customized R Markdown templates for authoring articles for Journal of Data Science.

r-jql 3.6.9
Propagated dependencies: r-randomforest@4.7-1.2 r-pdist@1.2.1 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=JQL
Licenses: LGPL 3
Build system: r
Synopsis: Jump Q-Learning for Individualized Interval-Valued Dose Rule
Description:

We provide tools to estimate the individualized interval-valued dose rule (I2DR) that maximizes the expected beneficial clinical outcome for each individual and returns an optimal interval-valued dose, by using the jump Q-learning (JQL) method. The jump Q-learning method directly models the conditional mean of the response given the dose level and the baseline covariates via jump penalized least squares regression under the framework of Q learning. We develop a searching algorithm by dynamic programming in order to find the optimal I2DR with the time complexity O(n2) and spatial complexity O(n). To alleviate the effects of misspecification of the Q-function, a residual jump Q-learning is further proposed to estimate the optimal I2DR. The outcome of interest includes the best partition of the entire dosage of interest, the regression coefficients of each partition, and the value function under the estimated I2DR as well as the Wald-type confidence interval of value function constructed through the Bootstrap.

r-jmbayes2 0.6-0
Propagated dependencies: r-survival@3.8-3 r-survc1@1.0-3 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-parallelly@1.45.1 r-nlme@3.1-168 r-matrixstats@1.5.0 r-mass@7.3-65 r-gridextra@2.3 r-glmmadaptive@0.9-7 r-ggplot2@4.0.1 r-coda@0.19-4.1 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://drizopoulos.github.io/JMbayes2/
Licenses: GPL 3+
Build system: r
Synopsis: Extended Joint Models for Longitudinal and Time-to-Event Data
Description:

Fit joint models for longitudinal and time-to-event data under the Bayesian approach. Multiple longitudinal outcomes of mixed type (continuous/categorical) and multiple event times (competing risks and multi-state processes) are accommodated. Rizopoulos (2012, ISBN:9781439872864).

r-jointmeancov 0.1.0
Propagated dependencies: r-glasso@1.11
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=jointMeanCov
Licenses: GPL 2
Build system: r
Synopsis: Joint Mean and Covariance Estimation for Matrix-Variate Data
Description:

Jointly estimates two-group means and covariances for matrix-variate data and calculates test statistics. This package implements the algorithms defined in Hornstein, Fan, Shedden, and Zhou (2018) <doi:10.1080/01621459.2018.1429275>.

r-jacpop 0.6
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=jacpop
Licenses: GPL 3
Build system: r
Synopsis: Jaccard Index for Population Structure Identification
Description:

Uses the Jaccard similarity index to account for population structure in sequencing studies. This method was specifically designed to detect population stratification based on rare variants, hence it will be especially useful in rare variant analysis.

r-json2args 0.3.0
Propagated dependencies: r-yaml@2.3.10 r-jsonlite@2.0.0
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://github.com/VForWaTer/json2aRgs
Licenses: GPL 3
Build system: r
Synopsis: Parse Parameters Inside a Docker Container
Description:

The function get_parameters() is intended to be used within a docker container to read keyword arguments from a .json file automagically. A tool.yaml file contains specifications on these keyword arguments, which are then passed as input to containerized R tools in the [tool-runner framework](<https://github.com/hydrocode-de/tool-runner>). A template for a containerized R tool, which can be used as a basis for developing new tools, is available at the following URL: <https://github.com/VForWaTer/tool_template_r>.

r-js 1.2.1
Propagated dependencies: r-v8@8.0.1
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://jeroen.r-universe.dev/js
Licenses: Expat
Build system: r
Synopsis: Tools for Working with JavaScript in R
Description:

This package provides a set of utilities for working with JavaScript syntax in R. Includes tools to parse, tokenize, compile, validate, reformat, optimize and analyze JavaScript code.

r-jskm 0.6.2
Propagated dependencies: r-survival@3.8-3 r-survey@4.4-8 r-patchwork@1.3.2 r-ggsci@4.1.0 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-cmprsk@2.2-12
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://github.com/jinseob2kim/jskm
Licenses: ASL 2.0
Build system: r
Synopsis: Kaplan-Meier Plot with 'ggplot2'
Description:

The function jskm() creates publication quality Kaplan-Meier plot with at risk tables below. svyjskm() provides plot for weighted Kaplan-Meier estimator.

r-juicyjuice 0.1.0
Propagated dependencies: r-v8@8.0.1
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://github.com/rich-iannone/juicyjuice
Licenses: Expat
Build system: r
Synopsis: Inline CSS Properties into HTML Tags Using 'juice'
Description:

There are occasions where you need a piece of HTML with integrated styles. A prime example of this is HTML email. This transformation involves moving the CSS and associated formatting instructions from the style block in the head of your document into the body of the HTML. Many prominent email clients require integrated styles in HTML email; otherwise a received HTML email will be displayed without any styling. This package will quickly and precisely perform these CSS transformations when given HTML text and it does so by using the JavaScript juice library.

r-ktensorgraphs 1.1
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=KTensorGraphs
Licenses: GPL 2+
Build system: r
Synopsis: Co-Tucker3 Analysis of Two Sequences of Matrices
Description:

This package provides a function called COTUCKER3() (Co-Inertia Analysis + Tucker3 method) which performs a Co-Tucker3 analysis of two sequences of matrices, as well as other functions called PCA() (Principal Component Analysis) and BGA() (Between-Groups Analysis), which perform analysis of one matrix, COIA() (Co-Inertia Analysis), which performs analysis of two matrices, PTA() (Partial Triadic Analysis), STATIS(), STATISDUAL() and TUCKER3(), which perform analysis of a sequence of matrices, and BGCOIA() (Between-Groups Co-Inertia Analysis), STATICO() (STATIS method + Co-Inertia Analysis), COSTATIS() (Co-Inertia Analysis + STATIS method), which also perform analysis of two sequences of matrices.

r-kwela 1.0.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/RFeissIV/KWELA
Licenses: Expat
Build system: r
Synopsis: Hierarchical Adaptive 'RT-QuIC' Classification for Complex Matrices
Description:

Extends RT-QuIC (Real-Time Quaking-Induced Conversion) statistical analysis to complex environmental matrices through hierarchical adaptive classification. KWELA is named after a deity of the Fore people of Papua New Guinea, among whom Kuru, a notable human prion disease, was identified. Implements a 6-layer architecture: hard gate biological constraints, per-well adaptive scoring, separation-aware combination, Youden-optimized cutoffs, replicate consensus, and matrix instability detection. Features dual-mode operation (diagnostic/research), auto-profile selection (Standard/Sensitive/Matrix-Robust), RAF integration for artifact detection, matrix-aware baseline correction, and multiple consensus rules. Methods include energy distance (Szekely and Rizzo (2013) <doi:10.1016/j.jspi.2013.03.018>), CRPS (Gneiting and Raftery (2007) <doi:10.1198/016214506000001437>), SSMD (Zhang (2007) <doi:10.1016/j.ygeno.2007.01.005>), and Jensen-Shannon divergence (Lin (1991) <doi:10.1109/18.61115>). This package implements methodology currently under peer review; please contact the author before publication using this approach. Development followed an iterative human-machine collaboration where all algorithmic design, statistical methodologies, and biological validation logic were conceptualized, tested, and iteratively refined by Richard A. Feiss through repeated cycles of running experimental data, evaluating analytical outputs, and selecting among candidate algorithms and approaches. AI systems ('Anthropic Claude and OpenAI GPT') served as coding assistants and analytical sounding boards under continuous human direction. The selection of statistical methods, evaluation of biological plausibility, and all final methodology decisions were made by the human author. AI systems did not independently originate algorithms, statistical approaches, or scientific methodologies.

r-koboconnectr 2.0.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/asitav-sen/KoboconnectR
Licenses: GPL 3+
Build system: r
Synopsis: Download Data from Kobotoolbox to R
Description:

Wrapper for Kobotoolbox APIs ver 2 mentioned at <https://support.kobotoolbox.org/api.html>, to download data from Kobotoolbox to R. Small and simple package that adds immense convenience for the data professionals using Kobotoolbox'.

r-kor-addrlink 1.0.1
Propagated dependencies: r-stringi@1.8.7 r-stringdist@0.9.15
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://git-kor.stadtdo.de
Licenses: GPL 3
Build system: r
Synopsis: Matching Address Data to Reference Index
Description:

Matches a data set with semi-structured address data, e.g., street and house number as a concatenated string, wrongly spelled street names or non-existing house numbers to a reference index. The methods are specifically designed for German municipalities ('KOR'-community) and German address schemes.

r-kyotil 2024.11-01
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://cran.r-project.org/package=kyotil
Licenses: GPL 2+
Build system: r
Synopsis: Utility Functions for Statistical Analysis Report Generation and Monte Carlo Studies
Description:

Helper functions for creating formatted summary of regression models, writing publication-ready tables to latex files, and running Monte Carlo experiments.

r-kesernetwork 0.1.0
Channel: guix-cran
Location: guix-cran/packages/k.scm (guix-cran packages k)
Home page: https://github.com/celehs/kesernetwork
Licenses: GPL 3+
Build system: r
Synopsis: Visualization of the KESER Network
Description:

This package provides a shiny app to visualize the knowledge networks for the code concepts. Using co-occurrence matrices of EHR codes from Veterans Affairs (VA) and Massachusetts General Brigham (MGB), the knowledge extraction via sparse embedding regression (KESER) algorithm was used to construct knowledge networks for the code concepts. Background and details about the method can be found at Chuan et al. (2021) <doi:10.1038/s41746-021-00519-z>.

Total packages: 69239