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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-cofast 0.2.0
Propagated dependencies: r-seurat@5.3.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-progress@1.2.3 r-profast@1.7 r-precast@1.8 r-pbapply@1.7-4 r-matrix@1.7-4 r-irlba@2.3.5.1 r-ggplot2@4.0.1 r-future@1.68.0 r-furrr@0.3.1 r-dr-sc@3.7 r-dplyr@1.1.4 r-ade4@1.7-23
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/feiyoung/coFAST
Licenses: GPL 3
Build system: r
Synopsis: Spatially-Aware Cell Clustering Algorithm with Cluster Significant Assessment
Description:

This package provides a spatially-aware cell clustering algorithm is provided with cluster significance assessment. It comprises four key modules: spatially-aware cell-gene co-embedding, cell clustering, signature gene identification, and cluster significant assessment. More details can be referred to Peng Xie, et al. (2025) <doi:10.1016/j.cell.2025.05.035>.

r-cencrne 1.0.0
Propagated dependencies: r-matrix@1.7-4 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=cencrne
Licenses: GPL 2
Build system: r
Synopsis: Consistent Estimation of the Number of Communities via Regularized Network Embedding
Description:

The network analysis plays an important role in numerous application domains including biomedicine. Estimation of the number of communities is a fundamental and critical issue in network analysis. Most existing studies assume that the number of communities is known a priori, or lack of rigorous theoretical guarantee on the estimation consistency. This method proposes a regularized network embedding model to simultaneously estimate the community structure and the number of communities in a unified formulation. The proposed model equips network embedding with a novel composite regularization term, which pushes the embedding vector towards its center and collapses similar community centers with each other. A rigorous theoretical analysis is conducted, establishing asymptotic consistency in terms of community detection and estimation of the number of communities. Reference: Ren, M., Zhang S. and Wang J. (2022). "Consistent Estimation of the Number of Communities via Regularized Network Embedding". Biometrics, <doi:10.1111/biom.13815>.

r-clustanalytics 0.5.5
Propagated dependencies: r-truncnorm@1.0-9 r-rdpack@2.6.4 r-rcpp@1.1.0 r-mclust@6.1.2 r-mcclust@1.0.1 r-igraph@2.2.1 r-fossil@0.4.0 r-dplyr@1.1.4 r-boot@1.3-32 r-aricode@1.0.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/martirm/clustAnalytics
Licenses: GPL 3+
Build system: r
Synopsis: Cluster Evaluation on Graphs
Description:

Evaluates the stability and significance of clusters on igraph graphs. Supports weighted and unweighted graphs. Implements the cluster evaluation methods defined by Arratia A, Renedo M (2021) <doi:10.7717/peerj-cs.600>. Also includes an implementation of the Reduced Mutual Information introduced by Newman et al. (2020) <doi:10.1103/PhysRevE.101.042304>.

r-chlorpromaziner 0.2.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://docs.ropensci.org/chlorpromazineR/
Licenses: GPL 3
Build system: r
Synopsis: Convert Antipsychotic Doses to Chlorpromazine Equivalents
Description:

As different antipsychotic medications have different potencies, the doses of different medications cannot be directly compared. Various strategies are used to convert doses into a common reference so that comparison is meaningful. Chlorpromazine (CPZ) has historically been used as a reference medication into which other antipsychotic doses can be converted, as "chlorpromazine-equivalent doses". Using conversion keys generated from widely-cited scientific papers, e.g. Gardner et. al 2010 <doi:10.1176/appi.ajp.2009.09060802> and Leucht et al. 2016 <doi:10.1093/schbul/sbv167>, antipsychotic doses are converted to CPZ (or any specified antipsychotic) equivalents. The use of the package is described in the included vignette. Not for clinical use.

r-cvlm 2.0.0
Propagated dependencies: r-rcppparallel@5.1.11-1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/phipnye/CV-LM
Licenses: Expat
Build system: r
Synopsis: Cross-Validation for Linear and Ridge Regression Models
Description:

This package implements cross-validation methods for linear and ridge regression models. The package provides grid-based selection of the ridge penalty parameter using Singular Value Decomposition (SVD) and supports K-fold cross-validation, Leave-One-Out Cross-Validation (LOOCV), and Generalized Cross-Validation (GCV). Computations are implemented in C++ via RcppArmadillo with optional parallelization using RcppParallel'. The methods are suitable for high-dimensional settings where the number of predictors exceeds the number of observations.

r-corset 0.1-5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=corset
Licenses: GPL 3
Build system: r
Synopsis: Arbitrary Bounding of Series and Time Series Objects
Description:

Set of methods to constrain numerical series and time series within arbitrary boundaries.

r-callme 0.1.11
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/coolbutuseless/callme
Licenses: Expat
Build system: r
Synopsis: Easily Compile and Call Inline 'C' Functions
Description:

Compile inline C code and easily call with automatically generated wrapper functions. By allowing user-defined headers and compilation flags (preprocessor, compiler and linking flags) the user can configure optimization options and linking to third party libraries. Multiple functions may be defined in a single block of code - which may be defined in a string or a path to a source file.

r-comfuncs 0.0.6
Propagated dependencies: r-shiny@1.11.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/TuCai/comFuncs
Licenses: Expat
Build system: r
Synopsis: Commonly Used Functions for R Shiny Applications
Description:

This package provides a set of common functions to be used for displaying messages, checking variables, finding absolute paths, starting applications, etc. More functions will be added later.

r-cgmissingdatar 0.0.1
Propagated dependencies: r-ranger@0.17.0 r-mice@3.18.0 r-metrics@0.1.4 r-fnn@1.1.4.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/saraswatsh/CGMissingDataR
Licenses: GPL 2+
Build system: r
Synopsis: Missingness Benchmark for Continuous Glucose Monitoring Data
Description:

Evaluates predictive performance under feature-level missingness in repeated-measures continuous glucose monitoring-like data. The benchmark injects missing values at user-specified rates, imputes incomplete feature matrices using an iterative chained-equations approach inspired by multivariate imputation by chained equations (MICE; Azur et al. (2011) <doi:10.1002/mpr.329>), fits Random Forest regression models (Breiman (2001) <doi:10.1023/A:1010933404324>) and k-nearest-neighbor regression models (Zhang (2016) <doi:10.21037/atm.2016.03.37>), and reports mean absolute percentage error and R-squared across missingness rates.

r-cautiouslearning 1.0.1
Propagated dependencies: r-spc@0.7.2 r-sitmo@2.0.2 r-rcpp@1.1.0 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CautiousLearning
Licenses: Expat
Build system: r
Synopsis: Control Charts with Guaranteed In-Control Performance and Cautious Parameters Learning
Description:

Design and use of control charts for detecting mean changes based on a delayed updating of the in-control parameter estimates. See Capizzi and Masarotto (2019) <doi:10.1080/00224065.2019.1640096> for the description of the method.

r-cerfit 0.1.1
Propagated dependencies: r-twang@2.6.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-randomforest@4.7-1.2 r-partykit@1.2-24 r-glmnet@4.1-10 r-cbps@0.24
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CERFIT
Licenses: GPL 2+
Build system: r
Synopsis: Causal Effect Random Forest of Interaction Trees
Description:

Fits a Causal Effect Random Forest of Interaction Tress (CERFIT) which is a modification of the Random Forest algorithm where each split is chosen to maximize subgroup treatment heterogeneity. Doing this allows it to estimate the individualized treatment effect for each observation in either randomized controlled trial (RCT) or observational data. For more information see L. Li, R. A. Levine, and J. Fan (2022) <doi:10.1002/sta4.457>.

r-copuladata 0.0-2
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://copula.r-forge.r-project.org/
Licenses: GPL 3+ FSDG-compatible
Build system: r
Synopsis: Data Sets for Copula Modeling
Description:

Data sets used for copula modeling in addition to those in the R package copula'. These include a random subsample from the US National Education Longitudinal Study (NELS) of 1988 and nursing home data from Wisconsin.

r-charlatan 0.6.2
Propagated dependencies: r-whisker@0.4.1 r-tibble@3.3.0 r-r6@2.6.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://docs.ropensci.org/charlatan/
Licenses: Expat
Build system: r
Synopsis: Make Fake Data
Description:

Make fake data that looks realistic, supporting addresses, person names, dates, times, colors, coordinates, currencies, digital object identifiers ('DOIs'), jobs, phone numbers, DNA sequences, doubles and integers from distributions and within a range.

r-chords 0.95.4
Propagated dependencies: r-matrix@1.7-4 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=chords
Licenses: GPL 2
Build system: r
Synopsis: Estimation in Respondent Driven Samples
Description:

Maximum likelihood estimation in respondent driven samples.

r-cusumdesign 1.1.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CUSUMdesign
Licenses: GPL 2
Build system: r
Synopsis: Compute Decision Interval and Average Run Length for CUSUM Charts
Description:

Computation of decision intervals (H) and average run lengths (ARL) for CUSUM charts. Details of the method are seen in Hawkins and Olwell (2012): Cumulative sum charts and charting for quality improvement, Springer Science & Business Media.

r-correctoverloadedpeaks 1.3.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/janlisec/CorrectOverloadedPeaks
Licenses: GPL 3
Build system: r
Synopsis: Correct Overloaded Peaks from GC-APCI-MS Data
Description:

Analyzes and modifies metabolomics raw data (generated using Gas Chromatography-Atmospheric Pressure Chemical Ionization-Mass Spectrometry) to correct overloaded signals, i.e. ion intensities exceeding detector saturation leading to a cut-off peak. Data in xcmsRaw format are accepted as input and mzXML files can be processed alternatively. Overloaded signals are detected automatically and modified using an Gaussian or an Isotopic-Ratio approach. Quality control plots are generated and corrected data are stored within the original xcmsRaw or mzXML respectively to allow further processing.

r-correlatio 0.2.1
Propagated dependencies: r-tibble@3.3.0 r-rdpack@2.6.4 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/mmiche/correlatio
Licenses: Expat
Build system: r
Synopsis: Visualize Details Behind Pearson's Correlation Coefficient
Description:

Helps visualizing what is summarized in Pearson's correlation coefficient. That is, it visualizes its main constituent, namely the distances of the single values to their respective mean. The visualization thereby shows what the etymology of the word correlation contains: In pairwise combination, bringing back (see package Vignette for more details). I hope that the correlatio package may benefit some people in understanding and critically evaluating what Pearson's correlation coefficient summarizes in a single number, i.e., to what degree and why Pearson's correlation coefficient may (or may not) be warranted as a measure of association.

r-cfr 0.2.0
Propagated dependencies: r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/epiverse-trace/cfr
Licenses: Expat
Build system: r
Synopsis: Estimate Disease Severity and Case Ascertainment
Description:

Estimate the severity of a disease and ascertainment of cases, as discussed in Nishiura et al. (2009) <doi:10.1371/journal.pone.0006852>.

r-cbctools 0.7.1
Propagated dependencies: r-rlang@1.1.6 r-randtoolbox@2.0.5 r-logitr@1.1.3 r-idefix@1.1.0 r-ggplot2@4.0.1 r-fastdummies@1.7.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/jhelvy/cbcTools
Licenses: Expat
Build system: r
Synopsis: Design and Analyze Choice-Based Conjoint Experiments
Description:

Design and evaluate choice-based conjoint survey experiments. Generate a variety of survey designs, including random designs, frequency-based designs, and D-optimal designs, as well as "labeled" designs (also known as "alternative-specific designs"), designs with "no choice" options, and designs with dominant alternatives removed. Conveniently inspect and compare designs using a variety of metrics, including design balance, overlap, and D-error, and simulate choice data for a survey design either randomly or according to a utility model defined by user-provided prior parameters. Conduct a power analysis for a given survey design by estimating the same model on different subsets of the data to simulate different sample sizes. Bayesian D-efficient designs using the cea and modfed methods are obtained using the idefix package by Traets et al (2020) <doi:10.18637/jss.v096.i03>. Choice simulation and model estimation in power analyses are handled using the logitr package by Helveston (2023) <doi:10.18637/jss.v105.i10>.

r-cfc 1.2.1
Propagated dependencies: r-survival@3.8-3 r-rcppprogress@0.4.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-foreach@1.5.2 r-doparallel@1.0.17 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CFC
Licenses: GPL 2+
Build system: r
Synopsis: Cause-Specific Framework for Competing-Risk Analysis
Description:

Numerical integration of cause-specific survival curves to arrive at cause-specific cumulative incidence functions, with three usage modes: 1) Convenient API for parametric survival regression followed by competing-risk analysis, 2) API for CFC, accepting user-specified survival functions in R, and 3) Same as 2, but accepting survival functions in C++. For mathematical details and software tutorial, see Mahani and Sharabiani (2019) <DOI:10.18637/jss.v089.i09>.

r-checkdown 0.0.13
Propagated dependencies: r-markdown@2.0 r-htmltools@0.5.8.1 r-glue@1.8.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://agricolamz.github.io/checkdown/
Licenses: GPL 2+
Build system: r
Synopsis: Check-Fields and Check-Boxes for 'rmarkdown'
Description:

This package creates auto-grading check-fields and check-boxes for rmarkdown or quarto HTML. It can be used in class, when teacher share materials and tasks, so students can solve some problems and check their work. In contrast to the learnr package, the checkdown package works serverlessly without shiny'.

r-controltest 1.1.0
Propagated dependencies: r-survival@3.8-3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=controlTest
Licenses: GPL 3
Build system: r
Synopsis: Quantile Comparison for Two-Sample Right-Censored Survival Data
Description:

Nonparametric two-sample procedure for comparing survival quantiles.

r-canprot 2.0.0
Propagated dependencies: r-stringi@1.8.7 r-multcompview@0.1-10
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/jedick/canprot
Licenses: GPL 3
Build system: r
Synopsis: Chemical Analysis of Proteins
Description:

Chemical analysis of proteins based on their amino acid compositions. Amino acid compositions can be read from FASTA files and used to calculate chemical metrics including carbon oxidation state and stoichiometric hydration state, as described in Dick et al. (2020) <doi:10.5194/bg-17-6145-2020>. Other properties that can be calculated include protein length, grand average of hydropathy (GRAVY), isoelectric point (pI), molecular weight (MW), standard molal volume (V0), and metabolic costs (Akashi and Gojobori, 2002 <doi:10.1073/pnas.062526999>; Wagner, 2005 <doi:10.1093/molbev/msi126>; Zhang et al., 2018 <doi:10.1038/s41467-018-06461-1>). A database of amino acid compositions of human proteins derived from UniProt is provided.

r-ctsmtmb 1.0.1
Propagated dependencies: r-zigg@0.0.2 r-tmb@1.9.18 r-stringr@1.6.0 r-rtmb@1.8 r-rcppxptrutils@0.1.3 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-r6@2.6.1 r-patchwork@1.3.2 r-matrix@1.7-4 r-ggplot2@4.0.1 r-ggfortify@0.4.19 r-geomtextpath@0.2.0 r-deriv@4.2.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/phillipbvetter/ctsmTMB
Licenses: GPL 3
Build system: r
Synopsis: Continuous Time Stochastic Modelling using Template Model Builder
Description:

Perform state and parameter inference, and forecasting, in stochastic state-space systems using the ctsmTMB class. This class, built with the R6 package, provides a user-friendly interface for defining and handling state-space models. Inference is based on maximum likelihood estimation, with derivatives efficiently computed through automatic differentiation enabled by the TMB'/'RTMB packages (Kristensen et al., 2016) <doi:10.18637/jss.v070.i05>. The available inference methods include Kalman filters, in addition to a Laplace approximation-based smoothing method. For further details of these methods refer to the documentation of the CTSMR package <https://ctsm.info/ctsmr-reference.pdf> and Thygesen (2025) <doi:10.48550/arXiv.2503.21358>. Forecasting capabilities include moment predictions and stochastic path simulations, both implemented in C++ using Rcpp (Eddelbuettel et al., 2018) <doi:10.1080/00031305.2017.1375990> for computational efficiency.

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