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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-cbl 0.1.3
Propagated dependencies: r-lightgbm@4.6.0 r-glmnet@4.1-10 r-foreach@1.5.2 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/dswatson/cbl
Licenses: GPL 3+
Build system: r
Synopsis: Causal Discovery under a Confounder Blanket
Description:

This package provides methods for learning causal relationships among a set of foreground variables X based on signals from a (potentially much larger) set of background variables Z, which are known non-descendants of X. The confounder blanket learner (CBL) uses sparse regression techniques to simultaneously perform many conditional independence tests, with complementary pairs stability selection to guarantee finite sample error control. CBL is sound and complete with respect to a so-called "lazy oracle", and works with both linear and nonlinear systems. For details, see Watson & Silva (2022) <arXiv:2205.05715>.

r-crc32c 0.0.3
Dependencies: cmake@4.1.3
Propagated dependencies: r-tidycpp@0.0.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/google/crc32c
Licenses: GPL 2+
Build system: r
Synopsis: Cyclic Redundancy Check with CPU-Specific Acceleration
Description:

Hardware-based support for CRC32C cyclic redundancy checksum function is made available for x86_64 systems with SSE2 support as well as for arm64', and detected at build-time via cmake with a software-based fallback. This functionality is exported at the C'-language level for use by other packages. CRC32C is described in RFC 3270 at <https://datatracker.ietf.org/doc/html/rfc3720> and is based on Castagnoli et al <doi:10.1109/26.231911>.

r-clustransition 1.0
Propagated dependencies: r-flexclust@1.5.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=clusTransition
Licenses: GPL 3
Build system: r
Synopsis: Monitor Changes in Cluster Solutions of Dynamic Datasets
Description:

Monitor and trace changes in clustering solutions of accumulating datasets at successive time points. The clusters can adopt External and Internal transition at succeeding time points. The External transitions comprise of Survived, Merged, Split, Disappeared, and newly Emerged candidates. In contrast, Internal transition includes changes in location and cohesion of the survived clusters. The package uses MONIC framework developed by Spiliopoulou, Ntoutsi, Theodoridis, and Schult (2006)<doi:10.1145/1150402.1150491> .

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-clump 0.8.1
Propagated dependencies: r-tableone@0.13.2 r-rlang@1.1.6 r-nbclust@3.0.1 r-mass@7.3-65 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-data-table@1.17.8 r-amap@0.8-20
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://arxiv.org/ftp/arxiv/papers/1807/1807.05926.pdf
Licenses: GPL 3+
Build system: r
Synopsis: Clustering of Micro Panel Data
Description:

Two-step feature-based clustering method designed for micro panel (longitudinal) data with the artificial panel data generator. See Sobisek, Stachova, Fojtik (2018) <arXiv:1807.05926>.

r-circacp 0.1.2
Propagated dependencies: r-tibble@3.3.0 r-pracma@2.4.6 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CircaCP
Licenses: GPL 3+
Build system: r
Synopsis: Sleep and Circadian Metrics Estimation from Actigraphy Data
Description:

This package provides a generic sleepâ wake cycle detection algorithm for analyzing unlabeled actigraphy data. The algorithm has been validated against event markers using data from the Multi-Ethnic Study of Atherosclerosis (MESA) Sleep study, and its methodological details are described in Chen and Sun (2024) <doi:10.1098/rsos.231468>. The package provides functions to estimate sleep metrics (e.g., sleep and wake onset times) and circadian rhythm metrics (e.g., mesor, phasor, interdaily stability, intradaily variability), as well as tools for screening actigraphy quality, fitting cosinor models, and performing parametric change point detection. The workflow can also be used to segment long actigraphy sequences into regularized structures for physical activity research.

r-chaosgame 1.5
Propagated dependencies: r-rgl@1.3.31 r-rcolorbrewer@1.1-3 r-plot3d@1.4.2 r-gridextra@2.3 r-ggplot2@4.0.1 r-colorramps@2.3.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=ChaosGame
Licenses: GPL 2
Build system: r
Synopsis: Chaos Game
Description:

The main objective of the package is to enter a word of at least two letters based on which an Iterated Function System with Probabilities is constructed, and a two-dimensional fractal containing the chosen word infinitely often is generated via the Chaos Game. Additionally, the package allows to project the two-dimensional fractal on several three-dimensional surfaces and to transform the fractal into another fractal with uniform marginals.

r-cloudml 0.7.1
Dependencies: python@3.11.14
Propagated dependencies: r-yaml@2.3.10 r-withr@3.0.2 r-tfruns@1.5.4 r-rstudioapi@0.17.1 r-rprojroot@2.1.1 r-processx@3.8.6 r-packrat@0.9.3 r-jsonlite@2.0.0 r-config@0.3.2
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/rstudio/cloudml
Licenses: ASL 2.0
Build system: r
Synopsis: Interface to the Google Cloud Machine Learning Platform
Description:

Interface to the Google Cloud Machine Learning Platform <https://cloud.google.com/vertex-ai>, which provides cloud tools for training machine learning models.

r-colorfindr 0.1.5
Propagated dependencies: r-treemap@2.4-4 r-tiff@0.1-12 r-tibble@3.3.0 r-stringr@1.6.0 r-rsvg@2.7.0 r-purrr@1.2.0 r-png@0.1-8 r-plotwidgets@0.5.1 r-plotly@4.11.0 r-pixmap@0.4-14 r-magrittr@2.0.4 r-jpeg@0.1-11 r-dplyr@1.1.4 r-bmp@0.3.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=colorfindr
Licenses: GPL 2+
Build system: r
Synopsis: Extract Colors from Windows BMP, JPEG, PNG, TIFF, and SVG Format Images
Description:

Extracts colors from various image types, returns customized reports and plots treemaps and 3D scatterplots of image compositions. Color palettes can also be created.

r-comradesm 0.1.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=ComradesM
Licenses: GPL 2+
Build system: r
Synopsis: The Comrades Marathon 1921 to 2019
Description:

Datasets related to the Comrades Marathon used in the book Antony Unwin (2024, ISBN:978-0367674007) "Getting (more out of) Graphics". The main dataset contains the times of every runner that finished in the time limit for each year the race was run.

r-carbayesdata 3.0
Propagated dependencies: r-sf@1.0-23
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CARBayesdata
Licenses: GPL 2+
Build system: r
Synopsis: Data Used in the Vignettes Accompanying the CARBayes and CARBayesST Packages
Description:

Spatio-temporal data from Scotland used in the vignettes accompanying the CARBayes (spatial modelling) and CARBayesST (spatio-temporal modelling) packages. Most of the data relate to the set of 271 Intermediate Zones (IZ) that make up the 2001 definition of the Greater Glasgow and Clyde health board.

r-cocron 1.0-1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: http://comparingcronbachalphas.org
Licenses: GPL 3+
Build system: r
Synopsis: Statistical Comparisons of Two or more Alpha Coefficients
Description:

Statistical tests for the comparison between two or more alpha coefficients based on either dependent or independent groups of individuals. A web interface is available at http://comparingcronbachalphas.org. A plugin for the R GUI and IDE RKWard is included. Please install RKWard from https:// rkward.kde.org to use this feature. The respective R package rkward cannot be installed directly from a repository, as it is a part of RKWard.

r-cortsinescore 0.1.0
Propagated dependencies: r-purrr@1.2.0 r-magrittr@2.0.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/simone-anza/CortSineScore
Licenses: Expat
Build system: r
Synopsis: Compute Cortisol Sine Score (CSS) for Diurnal Cortisol Analysis
Description:

Computes a single scalar metric for diurnal cortisol cycle analysis, the Cortisol Sine Score (CSS). The score is calculated as the sum over time points of concentration multiplied by sin(2 * pi * time / 24), giving positive weights to morning time points and negative weights to evening ones. The method is model-free, robust, and suitable for regression, classification, clustering, and biomarker research.

r-cpe 1.6.3
Propagated dependencies: r-survival@3.8-3 r-rms@8.1-0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CPE
Licenses: GPL 2+
Build system: r
Synopsis: Concordance Probability Estimates in Survival Analysis
Description:

Concordance probability estimate (CPE) is a commonly used performance measure in survival analysis that evaluates the predictive accuracy of a survival model. It measures how well a model can distinguish between pairs of individuals with different survival times. Specifically, it calculate the proportion of all pairs of individuals whose predicted survival times are correctly ordered.

r-clindr 2.5.2
Propagated dependencies: r-waiter@0.2.5-1.927501b r-tidyr@1.3.1 r-tibble@3.3.0 r-shiny@1.11.1 r-rstan@2.32.7 r-purrr@1.2.0 r-mvtnorm@1.3-3 r-glue@1.8.0 r-ggplot2@4.0.1 r-foreach@1.5.2 r-dplyr@1.1.4 r-dosefinding@1.4-1 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=clinDR
Licenses: GPL 2+
Build system: r
Synopsis: Simulation and Analysis Tools for Clinical Dose Response Modeling
Description:

Bayesian and ML Emax model fitting, graphics and simulation for clinical dose response. The summary data from the dose response meta-analyses in Thomas, Sweeney, and Somayaji (2014) <doi:10.1080/19466315.2014.924876> and Thomas and Roy (2016) <doi:10.1080/19466315.2016.1256229> Wu, Banerjee, Jin, Menon, Martin, and Heatherington(2017) <doi:10.1177/0962280216684528> are included in the package. The prior distributions for the Bayesian analyses default to the posterior predictive distributions derived from these references.

r-clustlearn 1.0.0
Propagated dependencies: r-proxy@0.4-27 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/Ediu3095/clustlearn
Licenses: Expat
Build system: r
Synopsis: Learn Clustering Techniques Through Examples and Code
Description:

Clustering methods, which (if asked) can provide step-by-step explanations of the algorithms used, as described in Ezugwu et. al., (2022) <doi:10.1016/j.engappai.2022.104743>; and datasets to test them on, which highlight the strengths and weaknesses of each technique, as presented in the clustering section of scikit-learn (Pedregosa et al., 2011) <https://jmlr.csail.mit.edu/papers/v12/pedregosa11a.html>.

r-copernicusr 0.1.0
Dependencies: python@3.11.14
Propagated dependencies: r-reticulate@1.44.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/HansTtito/copernicusR
Licenses: Expat
Build system: r
Synopsis: R Interface to Copernicus Marine Service
Description:

This package provides an R interface to the Copernicus Marine Service for downloading and accessing marine data. Integrates with the official copernicusmarine Python library through reticulate'. Requires Python 3.7+ and a free Copernicus Marine account. See <https://marine.copernicus.eu/> and <https://pypi.org/project/copernicusmarine/> for more information.

r-crsnls 0.2
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=crsnls
Licenses: GPL 2
Build system: r
Synopsis: Nonlinear Regression Parameters Estimation by 'CRS4HC' and 'CRS4HCe'
Description:

This package provides functions for nonlinear regression parameters estimation by algorithms based on Controlled Random Search algorithm. Both functions (crs4hc(), crs4hce()) adapt current search strategy by four heuristics competition. In addition, crs4hce() improves adaptability by adaptive stopping condition.

r-clttools 1.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=clttools
Licenses: GPL 2
Build system: r
Synopsis: Central Limit Theorem Experiments (Theoretical and Simulation)
Description:

Central limit theorem experiments presented by data frames or plots. Functions include generating theoretical sample space, corresponding probability, and simulated results as well.

r-ccoptimalmatch 0.1.0
Propagated dependencies: r-rlang@1.1.6 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=ccoptimalmatch
Licenses: GPL 2
Build system: r
Synopsis: Implementation of Case-Control Optimal Matching
Description:

Cases are matched to controls in an efficient, optimal and computationally flexible way. It uses the idea of sub-sampling in the level of the case, by creating pseudo-observations of controls. The user can select between replacement and without replacement, the number of controls, and several covariates to match upon. See Mamouris (2021) <doi:10.1186/s12874-021-01256-3> for an overview.

r-cmahalanobis 1.0.0
Propagated dependencies: r-reshape2@1.4.5 r-matrixstats@1.5.0 r-gridextra@2.3 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cmahalanobis
Licenses: GPL 3
Build system: r
Synopsis: Calculate Distance Measures for DataFrames
Description:

It provides functions that calculate Mahalanobis distance, Euclidean distance, Manhattan distance, Chebyshev distance, Hamming distance, Canberra distance, Minkowski dissimilarity (distance defined for p >= 1), Cosine dissimilarity, Bhattacharyya dissimilarity, Jaccard distance, Hellinger distance, Bray-Curtis dissimilarity, Sorensen-Dice dissimilarity between each pair of species in a list of data frames. These statistics are fundamental in various fields, such as cluster analysis, classification, and other applications of machine learning and data mining, where assessing similarity or dissimilarity between data is crucial. The package is designed to be flexible and easily integrated into data analysis workflows, providing reliable tools for evaluating distances in multidimensional contexts.

r-catirt 0.5.1
Propagated dependencies: r-numderiv@2016.8-1.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/swnydick/catIrt
Licenses: GPL 2+
Build system: r
Synopsis: Simulate IRT-Based Computerized Adaptive Tests
Description:

This package provides functions designed to simulate data that conform to basic unidimensional IRT models (for now 3-parameter binary response models and graded response models) along with Post-Hoc CAT simulations of those models given various item selection methods, ability estimation methods, and termination criteria. See Wainer (2000) <doi:10.4324/9781410605931>, van der Linden & Pashley (2010) <doi:10.1007/978-0-387-85461-8_1>, and Eggen (1999) <doi:10.1177/01466219922031365> for more details.

r-climatrends 1.2
Propagated dependencies: r-nasapower@4.2.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://agrdatasci.github.io/climatrends/
Licenses: Expat
Build system: r
Synopsis: Climate Variability Indices for Ecological Modelling
Description:

Supports analysis of trends in climate change, ecological and crop modelling.

r-cleancall 0.1.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/r-lib/cleancall#readme
Licenses: Expat
Build system: r
Synopsis: C Resource Cleanup via Exit Handlers
Description:

Wrapper of .Call() that runs exit handlers to clean up C resources. Helps managing C (non-R) resources while using the R API.

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Total results: 68655