_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
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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-jpsurv 3.0.20
Propagated dependencies: r-scales@1.4.0 r-ggrepel@0.9.6 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=JPSurv
Licenses: GPL 2+
Build system: r
Synopsis: Joinpoint Model for Relative and Cause-Specific Survival
Description:

This package contains functions for fitting a joinpoint proportional hazards model to relative survival or cause-specific survival data, including estimates of joinpoint years at which survival trends have changed and trend measures in the hazard and cumulative survival scale. See Yu et al.(2009) <doi:10.1111/j.1467-985X.2009.00580.x>.

r-jtdm 0.1-3
Propagated dependencies: r-reshape2@1.4.5 r-mvtnorm@1.3-3 r-mniw@1.0.2 r-gridextra@2.3 r-ggplot2@4.0.1 r-ggforce@0.5.0
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://github.com/giopogg/jtdm
Licenses: GPL 3
Build system: r
Synopsis: Joint Modelling of Functional Traits
Description:

Fitting and analyzing a Joint Trait Distribution Model. The Joint Trait Distribution Model is implemented in the Bayesian framework using conjugate priors and posteriors, thus guaranteeing fast inference. In particular the package computes joint probabilities and multivariate confidence intervals, and enables the investigation of how they depend on the environment through partial response curves. The method implemented by the package is described in Poggiato et al. (2023) <doi:10.1111/geb.13706>.

r-jstable 1.3.24
Propagated dependencies: r-tibble@3.3.0 r-tableone@0.13.2 r-survival@3.8-3 r-survey@4.4-8 r-rlang@1.1.6 r-purrr@1.2.0 r-nortest@1.0-4 r-magrittr@2.0.4 r-lmertest@3.1-3 r-lme4@1.1-37 r-labelled@2.16.0 r-geepack@1.3.13 r-dplyr@1.1.4 r-data-table@1.17.8 r-coxme@2.2-22 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://github.com/jinseob2kim/jstable
Licenses: ASL 2.0
Build system: r
Synopsis: Create Tables from Different Types of Regression
Description:

Create regression tables from generalized linear model(GLM), generalized estimating equation(GEE), generalized linear mixed-effects model(GLMM), Cox proportional hazards model, survey-weighted generalized linear model(svyglm) and survey-weighted Cox model results for publication.

r-jointpm 2.3.2
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=jointPm
Licenses: GPL 2+
Build system: r
Synopsis: Risk Estimation Using the Joint Probability Method
Description:

Estimate risk caused by two extreme and dependent forcing variables using bivariate extreme value models as described in Zheng, Westra, and Sisson (2013) <doi:10.1016/j.jhydrol.2013.09.054>; Zheng, Westra and Leonard (2014) <doi:10.1002/2013WR014616>; Zheng, Leonard and Westra (2015) <doi:10.2166/hydro.2015.052>.

r-jops 0.2.0
Propagated dependencies: r-spats@1.0-19 r-spam@2.11-1 r-rpart@4.1.24 r-mass@7.3-65 r-ggplot2@4.0.1 r-fields@17.1 r-fds@1.8 r-colorspace@2.1-2 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=JOPS
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Practical Smoothing with P-Splines
Description:

This package provides functions and data to reproduce all plots in the book "Practical Smoothing. The Joys of P-splines" by Paul H.C. Eilers and Brian D. Marx (2021, ISBN:978-1108482950).

r-jaya 1.0.3
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://github.com/neerajdhanraj/Jaya
Licenses: Expat
Build system: r
Synopsis: Gradient-Free Optimization Algorithm for Single and Multi-Objective Problems
Description:

An implementation of the Jaya optimization algorithm for both single-objective and multi-objective problems. Jaya is a population-based, gradient-free optimization algorithm capable of solving constrained and unconstrained optimization problems without hyperparameters. This package includes features such as multi-objective Pareto optimization, adaptive population adjustment, and early stopping. For further details, see R.V. Rao (2016) <doi:10.5267/j.ijiec.2015.8.004>.

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-janus 1.0.0
Propagated dependencies: r-tictoc@1.2.1 r-tensorflow@2.20.0 r-statrank@0.0.6 r-rmpfr@1.1-2 r-reticulate@1.44.1 r-readr@2.1.6 r-rcppalgos@2.9.3 r-purrr@1.2.0 r-narray@0.5.2 r-metrics@0.1.4 r-lubridate@1.9.4 r-keras@2.16.1 r-hash@2.2.6.3 r-ggplot2@4.0.1 r-forcats@1.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://rpubs.com/giancarlo_vercellino/janus
Licenses: GPL 3
Build system: r
Synopsis: Optimized Recommending System Based on 'tensorflow'
Description:

Proposes a coarse-to-fine optimization of a recommending system based on deep-neural networks using tensorflow'.

r-jrsicklsnmf 1.2.3
Propagated dependencies: r-umap@0.2.10.0 r-scran@1.38.0 r-rlang@1.1.6 r-rdpack@2.6.4 r-rcppprogress@0.4.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-pbapply@1.7-4 r-matrix@1.7-4 r-mass@7.3-65 r-kknn@1.4.1 r-irlba@2.3.5.1 r-igraph@2.2.1 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-foreach@1.5.2 r-factoextra@1.0.7 r-data-table@1.17.8 r-clvalid@0.7 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=jrSiCKLSNMF
Licenses: GPL 3
Build system: r
Synopsis: Multimodal Single-Cell Omics Dimensionality Reduction
Description:

This package provides methods to perform Joint graph Regularized Single-Cell Kullback-Leibler Sparse Non-negative Matrix Factorization ('jrSiCKLSNMF', pronounced "junior sickles NMF") on quality controlled single-cell multimodal omics count data. jrSiCKLSNMF specifically deals with dual-assay scRNA-seq and scATAC-seq data. This package contains functions to extract meaningful latent factors that are shared across omics modalities. These factors enable accurate cell-type clustering and facilitate visualizations. Methods for pre-processing, clustering, and mini-batch updates and other adaptations for larger datasets are also included. For further details on the methods used in this package please see Ellis, Roy, and Datta (2023) <doi:10.3389/fgene.2023.1179439>.

r-jackstrap 0.1.0
Propagated dependencies: r-tidyr@1.3.1 r-scales@1.4.0 r-rlang@1.1.6 r-reshape@0.8.10 r-plyr@1.8.9 r-ggplot2@4.0.1 r-foreach@1.5.2 r-fbasics@4041.97 r-dplyr@1.1.4 r-doparallel@1.0.17 r-benchmarking@0.33
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=jackstrap
Licenses: GPL 3
Build system: r
Synopsis: Correcting Nonparametric Frontier Measurements for Outliers
Description:

This package provides method used to check whether data have outlier in efficiency measurement of big samples with data envelopment analysis (DEA). In this jackstrap method, the package provides two criteria to define outliers: heaviside and k-s test. The technique was developed by Sousa and Stosic (2005) "Technical Efficiency of the Brazilian Municipalities: Correcting Nonparametric Frontier Measurements for Outliers." <doi:10.1007/s11123-005-4702-4>.

r-jlpm 1.0.2
Propagated dependencies: r-survival@3.8-3 r-stringr@1.6.0 r-randtoolbox@2.0.5 r-marqlevalg@2.0.8 r-lcmm@2.2.2
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=JLPM
Licenses: GPL 2+
Build system: r
Synopsis: Joint Latent Process Models
Description:

Estimation of extended joint models with shared random effects. Longitudinal data are handled in latent process models for continuous (Gaussian or curvilinear) and ordinal outcomes while proportional hazard models are used for the survival part. We propose a frequentist approach using maximum likelihood estimation. See Saulnier et al, 2022 <doi:10.1016/j.ymeth.2022.03.003>.

r-journalr 0.6.0
Propagated dependencies: r-glue@1.8.0 r-data-table@1.17.8 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://github.com/epi-sam/journalR
Licenses: Expat
Build system: r
Synopsis: Formatting Tools for Scientific Journal Writing
Description:

Scientific journal numeric formatting policies implemented in code. Emphasis on formatting mean/upper/lower sets of values to pasteable text for journal submission. For example c(2e6, 1e6, 3e6) becomes "2.00 million (1.00--3.00)". Lancet and Nature have built-in styles for rounding and punctuation marks. Users may extend journal styles arbitrarily. Four metrics are supported; proportions, percentage points, counts and rates. Magnitudes for all metrics are discovered automatically.

r-jmdem 1.0.1
Propagated dependencies: r-vgam@1.1-13 r-statmod@1.5.1
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=jmdem
Licenses: GPL 2
Build system: r
Synopsis: Fitting Joint Mean and Dispersion Effects Models
Description:

Joint mean and dispersion effects models fit the mean and dispersion parameters of a response variable by two separate linear models, the mean and dispersion submodels, simultaneously. It also allows the users to choose either the deviance or the Pearson residuals as the response variable of the dispersion submodel. Furthermore, the package provides the possibility to nest the submodels in one another, if one of the parameters has significant explanatory power on the other. Wu & Li (2016) <doi:10.1016/j.csda.2016.04.015>.

r-jadelizardoptions 1.0.1
Propagated dependencies: r-tibble@3.3.0 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=jadeLizardOptions
Licenses: GPL 3
Build system: r
Synopsis: Trading Jade Lizard Option Strategies
Description:

Jade Lizard and Reverse Jade Lizard Option Strategies are presented here through their Graphs. The graphic indicators, strategies, calculations, functions and all the discussions are for academic, research, and educational purposes only and should not be construed as investment advice and come with absolutely no Liability. Russell A. Stultz (â The option strategy desk reference: an essential reference for option traders (First edition.)â , 2019, ISBN: 9781949443912).

r-joyn 0.3.0
Propagated dependencies: r-rlang@1.1.6 r-lifecycle@1.0.4 r-glue@1.8.0 r-data-table@1.17.8 r-collapse@2.1.5 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://github.com/randrescastaneda/joyn
Licenses: Expat
Build system: r
Synopsis: Tool for Diagnosis of Tables Joins and Complementary Join Features
Description:

Tool for diagnosing table joins. It combines the speed of `collapse` and `data.table`, the flexibility of `dplyr`, and the diagnosis and features of the `merge` command in `Stata`.

r-jmatrix 1.5.2
Propagated dependencies: r-rcpp@1.1.0 r-memuse@4.2-3
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=jmatrix
Licenses: GPL 2+
Build system: r
Synopsis: Read from/Write to Disk Matrices with any Data Type in a Binary Format
Description:

This package provides a mainly instrumental package meant to allow other packages whose core is written in C++ to read, write and manipulate matrices in a binary format so that the memory used for them is no more than strictly needed. Its functionality is already inside parallelpam and scellpam', so if you have installed any of these, you do not need to install jmatrix'. Using just the needed memory is not always true with R matrices or vectors, since by default they are of double type. Trials like the float package have been done, but to use them you have to coerce a matrix already loaded in R memory to a float matrix, and then you can delete it. The problem comes when your computer has not memory enough to hold the matrix in the first place, so you are forced to load it by chunks. This is the problem this package tries to address (with partial success, but this is a difficult problem since R is not a strictly typed language, which is anyway quite hard to get in an interpreted language). This package allows the creation and manipulation of full, sparse and symmetric matrices of any standard data type.

r-joiner 1.2.8
Propagated dependencies: r-survival@3.8-3 r-statmod@1.5.1 r-nlme@3.1-168 r-mass@7.3-65 r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://github.com/graemeleehickey/joineR/
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Joint Modelling of Repeated Measurements and Time-to-Event Data
Description:

Analysis of repeated measurements and time-to-event data via random effects joint models. Fits the joint models proposed by Henderson and colleagues <doi:10.1093/biostatistics/1.4.465> (single event time) and by Williamson and colleagues (2008) <doi:10.1002/sim.3451> (competing risks events time) to a single continuous repeated measure. The time-to-event data is modelled using a (cause-specific) Cox proportional hazards regression model with time-varying covariates. The longitudinal outcome is modelled using a linear mixed effects model. The association is captured by a latent Gaussian process. The model is estimated using am Expectation Maximization algorithm. Some plotting functions and the variogram are also included. This project is funded by the Medical Research Council (Grant numbers G0400615 and MR/M013227/1).

r-jico 0.1
Propagated dependencies: r-rlist@0.4.6.2 r-nleqslv@3.3.5 r-matrix@1.7-4 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=JICO
Licenses: GPL 3+
Build system: r
Synopsis: Joint and Individual Regression
Description:

An R package that implements the JICO algorithm [Wang, P., Wang, H., Li, Q., Shen, D., & Liu, Y. (2024). <Journal of Computational and Graphical Statistics, 33(3), 763-773>]. It aims at solving the multi-group regression problem. The algorithm decomposes the responses from multiple groups into shared and group-specific components, which are driven by low-rank approximations of joint and individual structures from the covariates respectively.

r-jdcruncher 0.3.6
Propagated dependencies: r-openxlsx@4.2.8.1
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://github.com/InseeFr/JDCruncheR
Licenses: FSDG-compatible
Build system: r
Synopsis: Interface Between the 'JDemetra+' Cruncher and R, and Quality Report Generator
Description:

Tool for generating quality reports from cruncher outputs (and calculating series scores). The latest version of the cruncher can be downloaded here: <https://github.com/jdemetra/jwsacruncher/releases>.

r-jacquard 1.0.2
Propagated dependencies: r-rsolnp@2.0.1
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://www.r-project.org
Licenses: GPL 2+
Build system: r
Synopsis: Estimation of Jacquard's Genetic Identity Coefficients
Description:

This package contains procedures to estimate the nine condensed Jacquard genetic identity coefficients (Jacquard, 1974) <doi:10.1007/978-3-642-88415-3> by constrained least squares (Graffelman et al., 2024) <doi:10.1101/2024.03.25.586682> and by the method of moments (Csuros, 2014) <doi:10.1016/j.tpb.2013.11.001>. These procedures require previous estimation of the allele frequencies. Functions are supplied that estimate relationship parameters that derive from the Jacquard coefficients, such as individual inbreeding coefficients and kinship coefficients.

r-jamba 1.0.4
Propagated dependencies: r-withr@3.0.2 r-rcolorbrewer@1.1-3 r-kernsmooth@2.23-26 r-colorspace@2.1-2
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://jmw86069.github.io/jamba/
Licenses: Expat
Build system: r
Synopsis: Just Analysis Methods Base
Description:

Just analysis methods ('jam') base functions focused on bioinformatics. Version- and gene-centric alphanumeric sort, unique name and version assignment, colorized console and HTML output, color ramp and palette manipulation, Rmarkdown cache import, styled Excel worksheet import and export, interpolated raster output from smooth scatter and image plots, list to delimited vector, efficient list tools.

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-juliaformulae 0.1.0
Propagated dependencies: r-rrapply@1.2.8
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://cran.r-project.org/package=JuliaFormulae
Licenses: Expat
Build system: r
Synopsis: Translate R Regression Model Formulae to 'Julia' Syntax
Description:

Metaprogramming utilities for converting R regression model formulae to equivalents in Julia <doi:10.1137/141000671>, via modifications to the abstract syntax tree. Supports translations in zero correlation random effects syntax, protection of expressions to be evaluated as-is, interaction terms, and more. Accepts strings or R formula objects and returns modified R formula objects where possible (or a modified string, if not a valid formula in R).

r-jagstargets 1.2.2
Propagated dependencies: r-withr@3.0.2 r-tidyselect@1.2.1 r-tibble@3.3.0 r-targets@1.11.4 r-tarchetypes@0.13.2 r-secretbase@1.0.5 r-rlang@1.1.6 r-rjags@4-17 r-r2jags@0.8-9 r-qs2@0.1.6 r-purrr@1.2.0 r-posterior@1.6.1 r-fst@0.9.8 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://docs.ropensci.org/jagstargets/
Licenses: Expat
Build system: r
Synopsis: Targets for JAGS Pipelines
Description:

Bayesian data analysis usually incurs long runtimes and cumbersome custom code. A pipeline toolkit tailored to Bayesian statisticians, the jagstargets R package is leverages targets and R2jags to ease this burden. jagstargets makes it super easy to set up scalable JAGS pipelines that automatically parallelize the computation and skip expensive steps when the results are already up to date. Minimal custom code is required, and there is no need to manually configure branching, so usage is much easier than targets alone. For the underlying methodology, please refer to the documentation of targets <doi:10.21105/joss.02959> and JAGS (Plummer 2003) <https://www.r-project.org/conferences/DSC-2003/Proceedings/Plummer.pdf>.

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