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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-cryptorng 0.1.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/coolbutuseless/cryptorng
Licenses: Expat
Build system: r
Synopsis: Access System Cryptographic Pseudorandom Number Generators
Description:

Generate random numbers from the Cryptographically Secure Pseudorandom Number Generator (CSPRNG) provided by the underlying operating system. System CSPRNGs are seeded internally by the OS with entropy it gathers from the system hardware. The following system functions are used: arc4random_buf() on macOS and BSD; BCryptgenRandom() on Windows; Sys_getrandom() on Linux.

r-con2lki 0.1.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=con2lki
Licenses: Expat
Build system: r
Synopsis: Calculate the Dutch Air Quality Index (LKI)
Description:

Calculates the dutch air quality index (LKI). This index was created on the basis of scientific studies of the health effects of air pollution. From these studies it can be deduced at what concentrations a certain percentage of the population can be affected. For more information see: <https://www.rivm.nl/bibliotheek/rapporten/2014-0050.pdf>.

r-ca3variants 3.3.1
Propagated dependencies: r-plotly@4.11.0 r-multichull@3.0.1 r-gridextra@2.3 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-ggforce@0.5.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://www.R-project.org
Licenses: GPL 3+
Build system: r
Synopsis: Three-Way Correspondence Analysis Variants
Description:

This package provides four variants of three-way correspondence analysis (ca): three-way symmetrical ca, three-way non-symmetrical ca, three-way ordered symmetrical ca and three-way ordered non-symmetrical ca.

r-cats 1.0.2
Propagated dependencies: r-zoo@1.8-14 r-tidyr@1.3.1 r-purrr@1.2.0 r-plotly@4.11.0 r-openxlsx@4.2.8.1 r-mvtnorm@1.3-3 r-ggplot2@4.0.1 r-foreach@1.5.2 r-forcats@1.0.1 r-epitools@0.5-10.1 r-dplyr@1.1.4 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cats
Licenses: Expat
Build system: r
Synopsis: Cohort Platform Trial Simulation
Description:

Cohort plAtform Trial Simulation whereby every cohort consists of two arms, control and experimental treatment. Endpoints are co-primary binary endpoints and decisions are made using either Bayesian or frequentist decision rules. Realistic trial trajectories are simulated and the operating characteristics of the designs are calculated.

r-cenroc 2.0.0
Propagated dependencies: r-survival@3.8-3 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-icenreg@2.0.16 r-condsurv@2.0.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cenROC
Licenses: GPL 2+
Build system: r
Synopsis: Estimating Time-Dependent ROC Curve and AUC for Censored Data
Description:

This package contains functions to estimate a smoothed and a non-smoothed (empirical) time-dependent receiver operating characteristic curve and the corresponding area under the receiver operating characteristic curve and the optimal cutoff point for the right and interval censored survival data. See Beyene and El Ghouch (2020)<doi:10.1002/sim.8671> and Beyene and El Ghouch (2022) <doi:10.1002/bimj.202000382>.

r-causalhypergraph 0.1.0
Propagated dependencies: r-useful@1.2.6.1 r-stringr@1.6.0 r-diagrammersvg@0.1 r-diagrammer@1.0.11 r-cna@4.0.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=causalHyperGraph
Licenses: GPL 2+
Build system: r
Synopsis: Drawing Causal Hypergraphs
Description:

Draws causal hypergraph plots from models output by configurational comparative methods such as Coincidence Analysis (CNA) or Qualitative Comparative Analysis (QCA).

r-clustergvis 0.1.4
Propagated dependencies: r-tibble@3.3.0 r-singlecellexperiment@1.32.0 r-scales@1.4.0 r-reshape2@1.4.5 r-purrr@1.2.0 r-matrix@1.7-4 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-factoextra@1.0.7 r-e1071@1.7-16 r-dplyr@1.1.4 r-colorramps@2.3.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/junjunlab/ClusterGVis/
Licenses: Expat
Build system: r
Synopsis: One-Step to Cluster and Visualize Gene Expression Data
Description:

Streamlining the clustering and visualization of time-series gene expression data from RNA-Seq experiments, this tool supports fuzzy c-means and k-means clustering algorithms. It is compatible with outputs from widely-used packages such as Seurat', Monocle', and WGCNA', enabling seamless downstream visualization and analysis. See Lokesh Kumar and Matthias E Futschik (2007) <doi:10.6026/97320630002005> for more details.

r-clubpro 0.6.2
Propagated dependencies: r-rcppprogress@0.4.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://timbeechey.github.io/clubpro/
Licenses: GPL 3+
Build system: r
Synopsis: Classification Using Binary Procrustes Rotation
Description:

This package implements a classification method described by Grice (2011, ISBN:978-0-12-385194-9) using binary procrustes rotation; a simplified version of procrustes rotation.

r-clusterability 0.2.2.0
Propagated dependencies: r-sparsepca@0.1.2 r-elasticnet@1.3 r-diptest@0.77-2
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=clusterability
Licenses: GPL 2
Build system: r
Synopsis: Performs Tests for Cluster Tendency of a Data Set
Description:

Test for cluster tendency (clusterability) of a data set. The methods implemented - reducing the data set to a single dimension using principal component analysis or computing pairwise distances, and performing a multimodality test like the Dip Test or Silverman's Critical Bandwidth Test - are described in Adolfsson, Ackerman, and Brownstein (2019) <doi:10.1016/j.patcog.2018.10.026>. Such methods can inform whether clustering algorithms are appropriate for a data set.

r-csutil 2023.4.25
Propagated dependencies: r-magrittr@2.0.4 r-ggplot2@4.0.1 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://www.csids.no/csutil/
Licenses: Expat
Build system: r
Synopsis: Common Base-R Problems Relating to Lists
Description:

Utility functions that help with common base-R problems relating to lists. Lists in base-R are very flexible. This package provides functions to quickly and easily characterize types of lists. That is, to identify if all elements in a list are null, data.frames, lists, or fully named lists. Other functionality is provided for the handling of lists, such as the easy splitting of lists into equally sized groups, and the unnesting of data.frames within fully named lists.

r-crossexpression 1.0.0
Propagated dependencies: r-stringr@1.6.0 r-rfast@2.1.5.2 r-rann@2.6.2 r-matrix@1.7-4 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CrossExpression
Licenses: Expat
Build system: r
Synopsis: Cross-Expression Analysis of Spatial Transcriptomics Data
Description:

Analyzes spatial transcriptomic data using cells-by-genes and cell location matrices to find gene pairs that coordinate their expression between spatially adjacent cells. It enables quantitative analysis and graphical assessment of these cross-expression patterns. See Sarwar et al. (2025) <doi:10.1101/2024.09.17.613579> and <https://github.com/gillislab/CrossExpression/> for more details.

r-circles 0.1.0
Propagated dependencies: r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/ryan-odea/circles
Licenses: Expat
Build system: r
Synopsis: Small Package for Drawing Various Combinations of Circles
Description:

This package contains the adaptation of bubblebath from MATLAB', developed by Adam Danz and available through the MATLAB Central File Exchange, and the tools to transform a dataframe of radii and points to plot-able paths.

r-chouca 0.1.99
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-plyr@1.8.9 r-digest@0.6.39
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/alexgenin/chouca
Licenses: GPL 3+
Build system: r
Synopsis: Stochastic Cellular Automaton Engine
Description:

An engine for stochastic cellular automata. It provides a high-level interface to declare a model, which can then be simulated by various backends (Genin et al. (2023) <doi:10.1101/2023.11.08.566206>).

r-cir 2.5.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cir
Licenses: GPL 2
Build system: r
Synopsis: Centered Isotonic Regression and Dose-Response Utilities
Description:

Isotonic regression (IR) and its improvement: centered isotonic regression (CIR). CIR is recommended in particular with small samples. Also, interval estimates for both, and additional utilities such as plotting dose-response data. For dev version and change history, see GitHub assaforon/cir.

r-cosimmr 1.0.12
Propagated dependencies: r-viridis@0.6.5 r-reshape2@1.4.5 r-rcppdist@0.1.1.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-r2jags@0.8-9 r-ggplot2@4.0.1 r-ggnewscale@0.5.2 r-checkmate@2.3.3 r-bayesplot@1.14.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/emmagovan/cosimmr
Licenses: GPL 2+
Build system: r
Synopsis: Fast Fitting of Stable Isotope Mixing Models with Covariates
Description:

Fast fitting of Stable Isotope Mixing Models in R. Allows for the inclusion of covariates. Also has built-in summary functions and plot functions which allow for the creation of isospace plots. Variational Bayes is used to fit these models, methods as described in: Tran et al., (2021) <doi:10.48550/arXiv.2103.01327>.

r-compound-cox 3.33
Propagated dependencies: r-survival@3.8-3 r-numderiv@2016.8-1.1 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=compound.Cox
Licenses: GPL 2
Build system: r
Synopsis: Univariate Feature Selection and Compound Covariate for Predicting Survival, Including Copula-Based Analyses for Dependent Censoring
Description:

Univariate feature selection and compound covariate methods under the Cox model with high-dimensional features (e.g., gene expressions). Available are survival data for non-small-cell lung cancer patients with gene expressions (Chen et al 2007 New Engl J Med) <DOI:10.1056/NEJMoa060096>, statistical methods in Emura et al (2012 PLoS ONE) <DOI:10.1371/journal.pone.0047627>, Emura & Chen (2016 Stat Methods Med Res) <DOI:10.1177/0962280214533378>, and Emura et al (2019)<DOI:10.1016/j.cmpb.2018.10.020>. Algorithms for generating correlated gene expressions are also available. Estimation of survival functions via copula-graphic (CG) estimators is also implemented, which is useful for sensitivity analyses under dependent censoring (Yeh et al 2023 Biomedicines) <DOI:10.3390/biomedicines11030797> and factorial survival analyses (Emura et al 2024 Stat Methods Med Res) <DOI:10.1177/09622802231215805>.

r-crwrm 0.0.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CRWRM
Licenses: GPL 3
Build system: r
Synopsis: Changing the Reference Group without Re-Running the Model
Description:

To re-calculate the coefficients and the standard deviation when changing the reference group.

r-cytometree 2.0.6
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mclust@6.1.2 r-igraph@2.2.1 r-gofkernel@2.1-3 r-ggplot2@4.0.1 r-cowplot@1.2.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://sistm.github.io/cytometree/
Licenses: LGPL 3 FSDG-compatible
Build system: r
Synopsis: Automated Cytometry Gating and Annotation
Description:

Given the hypothesis of a bi-modal distribution of cells for each marker, the algorithm constructs a binary tree, the nodes of which are subpopulations of cells. At each node, observed cells and markers are modeled by both a family of normal distributions and a family of bi-modal normal mixture distributions. Splitting is done according to a normalized difference of AIC between the two families. Method is detailed in: Commenges, Alkhassim, Gottardo, Hejblum & Thiebaut (2018) <doi: 10.1002/cyto.a.23601>.

r-confidenceellipse 1.1.0
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-rgl@1.3.31 r-purrr@1.2.0 r-pcapp@2.0-5 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-forcats@1.0.1 r-dplyr@1.1.4 r-cellwise@2.5.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://christiangoueguel.github.io/ConfidenceEllipse/
Licenses: Expat
Build system: r
Synopsis: Computation of 2D and 3D Elliptical Joint Confidence Regions
Description:

Computing elliptical joint confidence regions at a specified confidence level. It provides the flexibility to estimate either classical or robust confidence regions, which can be visualized in 2D or 3D plots. The classical approach assumes normality and uses the mean and covariance matrix to define the confidence regions. Alternatively, the robustified version employs estimators like minimum covariance determinant (MCD) and M-estimator, making them less sensitive to outliers and departures from normality. Furthermore, the functions allow users to group the dataset based on categorical variables and estimate separate confidence regions for each group. This capability is particularly useful for exploring potential differences or similarities across subgroups within a dataset. Varmuza and Filzmoser (2009, ISBN:978-1-4200-5947-2). Johnson and Wichern (2007, ISBN:0-13-187715-1). Raymaekers and Rousseeuw (2019) <DOI:10.1080/00401706.2019.1677270>.

r-concaveman 1.2.0
Dependencies: geos@3.12.1 gdal@3.8.2
Propagated dependencies: r-v8@8.0.1 r-sf@1.0-23 r-jsonlite@2.0.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://joelgombin.github.io/concaveman/
Licenses: GPL 3
Build system: r
Synopsis: Very Fast 2D Concave Hull Algorithm
Description:

The concaveman function ports the concaveman (<https://github.com/mapbox/concaveman>) library from mapbox'. It computes the concave polygon(s) for one or several set of points.

r-coxphf 1.13.4
Propagated dependencies: r-tibble@3.3.0 r-survival@3.8-3 r-generics@0.1.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cemsiis.meduniwien.ac.at/kb/wf/software/statistische-software/fccoxphf/
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Cox Regression with Firth's Penalized Likelihood
Description:

This package implements Firth's penalized maximum likelihood bias reduction method for Cox regression which has been shown to provide a solution in case of monotone likelihood (nonconvergence of likelihood function), see Heinze and Schemper (2001) and Heinze and Dunkler (2008). The program fits profile penalized likelihood confidence intervals which were proved to outperform Wald confidence intervals.

r-catdyn 1.1-1
Propagated dependencies: r-optimx@2025-4.9 r-bb@2019.10-1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CatDyn
Licenses: GPL 2+
Build system: r
Synopsis: Fishery Stock Assessment by Catch Dynamics Models
Description:

Based on fishery Catch Dynamics instead of fish Population Dynamics (hence CatDyn) and using high-frequency or medium-frequency catch in biomass or numbers, fishing nominal effort, and mean fish body weight by time step, from one or two fishing fleets, estimate stock abundance, natural mortality rate, and fishing operational parameters. It includes methods for data organization, plotting standard exploratory and analytical plots, predictions, for 100 types of models of increasing complexity, and 72 likelihood models for the data.

r-covsim 1.1.0
Propagated dependencies: r-tmvtnorm@1.7 r-rvinecopulib@0.7.3.1.0 r-pearsonds@1.3.2 r-nleqslv@3.3.5 r-matrix@1.7-4 r-mass@7.3-65 r-lavaan@0.6-20
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=covsim
Licenses: GPL 2+
Build system: r
Synopsis: VITA, IG and PLSIM Simulation for Given Covariance and Marginals
Description:

Random sampling from distributions with user-specified population covariance matrix. Marginal information may be fully specified, for which the package implements the VITA (VIne-To-Anything) algorithm Grønneberg and Foldnes (2017) <doi:10.1007/s11336-017-9569-6>. See also Grønneberg, Foldnes and Marcoulides (2022) <doi:10.18637/jss.v102.i03>. Alternatively, marginal skewness and kurtosis may be specified, for which the package implements the IG (independent generator) and PLSIM (piecewise linear) algorithms, see Foldnes and Olsson (2016) <doi:10.1080/00273171.2015.1133274> and Foldnes and Grønneberg (2021) <doi:10.1080/10705511.2021.1949323>, respectively.

r-crassmat 0.0.6
Propagated dependencies: r-svmisc@1.4.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=crassmat
Licenses: GPL 3
Build system: r
Synopsis: Conditional Random Sampling Sparse Matrices
Description:

Conducts conditional random sampling on observed values in sparse matrices. Useful for training and test set splitting sparse matrices prior to model fitting in cross-validation procedures and estimating the predictive accuracy of data imputation methods, such as matrix factorization or singular value decomposition (SVD). Although designed for applications with sparse matrices, CRASSMAT can also be applied to complete matrices, as well as to those containing missing values.

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