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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-clusterv 1.1.1
Propagated dependencies: r-mass@7.3-65 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://valentini.di.unimi.it/SW/clusterv/
Licenses: GPL 2+
Build system: r
Synopsis: Assessment of Cluster Stability by Randomized Maps
Description:

The reliability of clusters is estimated using random projections. A set of stability measures is provided to assess the reliability of the clusters discovered by a generic clustering algorithm. The stability measures are taylored to high dimensional data (e.g. DNA microarray data) (Valentini, G (2005), <doi:10.1093/bioinformatics/bti817>.

r-cartographr 0.2.4
Propagated dependencies: r-sysfonts@0.8.9 r-showtext@0.9-7 r-sf@1.0-23 r-osmdata@0.3.0 r-httr2@1.2.1 r-ggplot2@4.0.1 r-curl@7.0.0 r-crayon@1.5.3 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://da-wi.github.io/cartographr/
Licenses: GPL 3+
Build system: r
Synopsis: Crafting Print-Ready Maps and Layered Visualizations
Description:

Simplifying the creation of print-ready maps, this package offers a user-friendly interface derived from ggplot2 for handling OpenStreetMap data. It streamlines the map-making process, allowing users to focus on the story their maps tell. Transforming raw geospatial data into informative visualizations is made easy with simple features sf geometries. Whether for urban planning, environmental studies, or impactful public presentations, this tool facilitates straightforward and effective map creation. Enhance the dissemination of spatial information with high-quality, narrative-driven visualizations!

r-catalytic 0.1.0
Propagated dependencies: r-truncnorm@1.0-9 r-survival@3.8-3 r-rstan@2.32.7 r-rlang@1.1.6 r-quadform@0.0-4 r-mass@7.3-65 r-lme4@1.1-37 r-invgamma@1.2 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=catalytic
Licenses: Expat
Build system: r
Synopsis: Tools for Applying Catalytic Priors in Statistical Modeling
Description:

To improve estimation accuracy and stability in statistical modeling, catalytic prior distributions are employed, integrating observed data with synthetic data generated from a simpler model's predictive distribution. This approach enhances model robustness, stability, and flexibility in complex data scenarios. The catalytic prior distributions are introduced by Huang et al. (2020, <doi:10.1073/pnas.1920913117>), Li and Huang (2023, <doi:10.48550/arXiv.2312.01411>).

r-coarsedatatools 0.7.2
Propagated dependencies: r-mcmcpack@1.7-1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: http://nickreich.github.io/coarseDataTools/
Licenses: GPL 2+
Build system: r
Synopsis: Analysis of Coarsely Observed Data
Description:

This package provides functions to analyze coarse data. Specifically, it contains functions to (1) fit parametric accelerated failure time models to interval-censored survival time data, and (2) estimate the case-fatality ratio in scenarios with under-reporting. This package's development was motivated by applications to infectious disease: in particular, problems with estimating the incubation period and the case fatality ratio of a given disease. Sample data files are included in the package. See Reich et al. (2009) <doi:10.1002/sim.3659>, Reich et al. (2012) <doi:10.1111/j.1541-0420.2011.01709.x>, and Lessler et al. (2009) <doi:10.1016/S1473-3099(09)70069-6>.

r-comparecausalnetworks 0.2.6.2
Propagated dependencies: r-matrix@1.7-4 r-expm@1.0-0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/christinaheinze/CompareCausalNetworks
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Interface to Diverse Estimation Methods of Causal Networks
Description:

Unified interface for the estimation of causal networks, including the methods backShift (from package backShift'), bivariateANM (bivariate additive noise model), bivariateCAM (bivariate causal additive model), CAM (causal additive model) (from package CAM'; the package is temporarily unavailable on the CRAN repository; formerly available versions can be obtained from the archive), hiddenICP (invariant causal prediction with hidden variables), ICP (invariant causal prediction) (from package InvariantCausalPrediction'), GES (greedy equivalence search), GIES (greedy interventional equivalence search), LINGAM', PC (PC Algorithm), FCI (fast causal inference), RFCI (really fast causal inference) (all from package pcalg') and regression.

r-causens 0.0.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://kuan-liu-lab.github.io/causens/
Licenses: Expat
Build system: r
Synopsis: Perform Causal Sensitivity Analyses Using Various Statistical Methods
Description:

While data from randomized experiments remain the gold standard for causal inference, estimation of causal estimands from observational data is possible through various confounding adjustment methods. However, the challenge of unmeasured confounding remains a concern in causal inference, where failure to account for unmeasured confounders can lead to biased estimates of causal estimands. Sensitivity analysis within the framework of causal inference can help adjust for possible unmeasured confounding. In `causens`, three main methods are implemented: adjustment via sensitivity functions (Brumback, Hernán, Haneuse, and Robins (2004) <doi:10.1002/sim.1657> and Li, Shen, Wu, and Li (2011) <doi:10.1093/aje/kwr096>), Bayesian parametric modelling and Monte Carlo approaches (McCandless, Lawrence C and Gustafson, Paul (2017) <doi:10.1002/sim.7298>).

r-ci 0.0.1
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-purrr@1.2.0 r-forcats@1.0.1 r-dplyr@1.1.4 r-desctools@0.99.60 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/GegznaV/ci
Licenses: GPL 3+
Build system: r
Synopsis: Confidence Intervals for Education
Description:

An educational package providing intuitive functions for calculating confidence intervals (CI) for various statistical parameters. Designed primarily for teaching and learning about statistical inference (particularly confidence intervals). Offers user-friendly wrappers around established methods for proportions, means, and bootstrap-based intervals. Integrates seamlessly with Tidyverse workflows, making it ideal for classroom demonstrations and student exercises.

r-caramel 1.4
Propagated dependencies: r-geometry@0.5.2
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/fzao/caRamel
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Automatic Calibration by Evolutionary Multi Objective Algorithm
Description:

The caRamel optimizer has been developed to meet the requirement for an automatic calibration procedure that delivers a family of parameter sets that are optimal with regard to a multi-objective target (Monteil et al. <doi:10.5194/hess-24-3189-2020>).

r-cms 0.1.0
Propagated dependencies: r-xml2@1.5.0 r-rvest@1.0.5 r-rlang@1.1.6 r-readr@2.1.6 r-magrittr@2.0.4 r-dplyr@1.1.4 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/subramv/cms
Licenses: GPL 3
Build system: r
Synopsis: Calculate Medicare Reimbursement
Description:

Uses the CMS application programming interface <https://dnav.cms.gov/api/healthdata> to provide users databases containing yearly Medicare reimbursement rates in the United States. Data can be acquired for the entire United States or only for specific localities. Currently, support is only provided for the Medicare Physician Fee Schedule, but support will be expanded for other CMS databases in future versions.

r-c3net 1.1.1.1
Propagated dependencies: r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=c3net
Licenses: GPL 3+
Build system: r
Synopsis: Inferring Large-Scale Gene Networks with C3NET
Description:

Allows inferring gene regulatory networks with direct physical interactions from microarray expression data using C3NET.

r-coxmk 0.1.1
Propagated dependencies: r-survival@3.8-3 r-matrix@1.7-4 r-irlba@2.3.5.1 r-gdsfmt@1.46.0 r-bedmatrix@2.0.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=CoxMK
Licenses: GPL 3
Build system: r
Synopsis: Model-X Knockoff Method for Genome-Wide Survival Association Analysis
Description:

This package provides a genome-wide survival framework that integrates sequential conditional independent tuples and saddlepoint approximation method, to provide SNP-level false discovery rate control while improving power, particularly for biobank-scale survival analyses with low event rates. The method is based on model-X knockoffs as described in Barber and Candes (2015) <doi:10.1214/15-AOS1337> and fast survival analysis methods from Bi et al. (2020) <doi:10.1016/j.ajhg.2020.06.003>. A shrinkage algorithmic leveraging accelerates multiple knockoffs generation in large genetic cohorts. This CRAN version uses standard Cox regression for association testing. For enhanced performance on very large datasets, users may optionally install the SPACox package from GitHub which provides saddlepoint approximation methods for survival analysis.

r-cito 1.1
Propagated dependencies: r-torchvision@0.8.0 r-torch@0.16.3 r-tibble@3.3.0 r-progress@1.2.3 r-parabar@1.4.2 r-lme4@1.1-37 r-gridextra@2.3 r-coro@1.1.0 r-cli@3.6.5 r-checkmate@2.3.3 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://citoverse.github.io/cito/
Licenses: GPL 3+
Build system: r
Synopsis: Building and Training Neural Networks
Description:

The cito package provides a user-friendly interface for training and interpreting deep neural networks (DNN). cito simplifies the fitting of DNNs by supporting the familiar formula syntax, hyperparameter tuning under cross-validation, and helps to detect and handle convergence problems. DNNs can be trained on CPU, GPU and MacOS GPUs. In addition, cito has many downstream functionalities such as various explainable AI (xAI) metrics (e.g. variable importance, partial dependence plots, accumulated local effect plots, and effect estimates) to interpret trained DNNs. cito optionally provides confidence intervals (and p-values) for all xAI metrics and predictions. At the same time, cito is computationally efficient because it is based on the deep learning framework torch'. The torch package is native to R, so no Python installation or other API is required for this package.

r-constructive 1.3.0
Propagated dependencies: r-waldo@0.6.2 r-rlang@1.1.6 r-diffobj@0.3.6 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/cynkra/constructive
Licenses: Expat
Build system: r
Synopsis: Display Idiomatic Code to Construct Most R Objects
Description:

Prints code that can be used to recreate R objects. In a sense it is similar to base::dput() or base::deparse() but constructive strives to use idiomatic constructors.

r-cgwtools 4.1
Propagated dependencies: r-gmp@0.7-5
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cgwtools
Licenses: LGPL 3
Build system: r
Synopsis: Miscellaneous Tools
Description:

This package provides functions for performing quick observations or evaluations of data, including a variety of ways to list objects by size, class, etc. The functions seqle and reverse.seqle mimic the base rle but can search for linear sequences. The function splatnd allows the user to generate zero-argument commands without the need for makeActiveBinding . Functions provided to convert from any base to any other base, and to find the n-th greatest max or n-th least min. In addition, functions which mimic Unix shell commands, including head', tail ,'pushd ,and popd'. Various other goodies included as well.

r-ceterisparibus 0.6
Propagated dependencies: r-gower@1.0.2 r-ggplot2@4.0.1 r-dalex@2.5.3
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://pbiecek.github.io/ceterisParibus/
Licenses: GPL 2
Build system: r
Synopsis: Ceteris Paribus Profiles
Description:

Ceteris Paribus Profiles (What-If Plots) are designed to present model responses around selected points in a feature space. For example around a single prediction for an interesting observation. Plots are designed to work in a model-agnostic fashion, they are working for any predictive Machine Learning model and allow for model comparisons. Ceteris Paribus Plots supplement the Break Down Plots from breakDown package.

r-curephem 0.3.2
Propagated dependencies: r-survival@3.8-3 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=curephEM
Licenses: GPL 2
Build system: r
Synopsis: NPMLE for Logistic-Cox Cure-Rate Model
Description:

Expectation-Maximization (EM) algorithm for point estimation and variance estimation to the nonparametric maximum likelihood estimator (NPMLE) for logistic-Cox cure-rate model with left truncation and right- censoring. See Hou, Chambers and Xu (2017) <doi:10.1007/s10985-017-9415-2>.

r-curstatci 0.1.1
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/kimhendrickx/curstatCI
Licenses: GPL 3
Build system: r
Synopsis: Confidence Intervals for the Current Status Model
Description:

Computes the maximum likelihood estimator, the smoothed maximum likelihood estimator and pointwise bootstrap confidence intervals for the distribution function under current status data. Groeneboom and Hendrickx (2017) <doi:10.1214/17-EJS1345>.

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-condoroptions 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/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=condorOptions
Licenses: GPL 3
Build system: r
Synopsis: Trading Condor Options Strategies
Description:

Trading of Condor Options Strategies is represented 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. Guy Cohen (â The Bible of Options Strategies (2nd ed.)â , 2015, ISBN: 9780133964028). Zura Kakushadze, Juan A. Serur (â 151 Trading Strategiesâ , 2018, ISBN: 9783030027919). John C. Hull (â Options, Futures, and Other Derivatives (11th ed.)â , 2022, ISBN: 9780136939979).

r-celltrackr 1.2.2
Propagated dependencies: r-pracma@2.4.6 r-ellipse@0.5.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: http://www.motilitylab.net
Licenses: GPL 2
Build system: r
Synopsis: Motion Trajectory Analysis
Description:

This package provides methods for analyzing (cell) motion in two or three dimensions. Available measures include displacement, confinement ratio, autocorrelation, straightness, turning angle, and fractal dimension. Measures can be applied to entire tracks, steps, or subtracks with varying length. While the methodology has been developed for cell trajectory analysis, it is applicable to anything that moves including animals, people, or vehicles. Some of the methodology implemented in this packages was described by: Beauchemin, Dixit, and Perelson (2007) <doi:10.4049/jimmunol.178.9.5505>, Beltman, Maree, and de Boer (2009) <doi:10.1038/nri2638>, Gneiting and Schlather (2004) <doi:10.1137/S0036144501394387>, Mokhtari, Mech, Zitzmann, Hasenberg, Gunzer, and Figge (2013) <doi:10.1371/journal.pone.0080808>, Moreau, Lemaitre, Terriac, Azar, Piel, Lennon-Dumenil, and Bousso (2012) <doi:10.1016/j.immuni.2012.05.014>, Textor, Peixoto, Henrickson, Sinn, von Andrian, and Westermann (2011) <doi:10.1073/pnas.1102288108>, Textor, Sinn, and de Boer (2013) <doi:10.1186/1471-2105-14-S6-S10>, Textor, Henrickson, Mandl, von Andrian, Westermann, de Boer, and Beltman (2014) <doi:10.1371/journal.pcbi.1003752>.

r-cvap 0.1.6
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-rlang@1.1.6 r-readr@2.1.6 r-fs@1.6.6 r-dplyr@1.1.4 r-cli@3.6.5 r-censable@0.0.8
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://github.com/christopherkenny/cvap
Licenses: Expat
Build system: r
Synopsis: Citizen Voting Age Population
Description:

Works with the Citizen Voting Age Population special tabulation from the US Census Bureau <https://www.census.gov/programs-surveys/decennial-census/about/voting-rights/cvap.html>. Provides tools to download and process raw data. Also provides a downloading interface to processed data. Implements a very basic approach to estimate block level citizen voting age population from block group data.

r-channelattributionapp 1.3
Propagated dependencies: r-shiny@1.11.1 r-ggplot2@4.0.1 r-data-table@1.17.8 r-channelattribution@2.2.4
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: http://www.channelattribution.net
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Shiny Web Application for the Multichannel Attribution Problem
Description:

Shiny Web Application for the Multichannel Attribution Problem. It is a user-friendly graphical interface for package ChannelAttribution'.

r-cvmgof 1.0.3
Propagated dependencies: r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: https://cran.r-project.org/package=cvmgof
Licenses: CeCILL
Build system: r
Synopsis: Cramer-von Mises Goodness-of-Fit Tests
Description:

It is devoted to Cramer-von Mises goodness-of-fit tests. It implements three statistical methods based on Cramer-von Mises statistics to estimate and test a regression model.

r-cprr 0.2.0
Channel: guix-cran
Location: guix-cran/packages/c.scm (guix-cran packages c)
Home page: http://github.com/anhoej/cprr
Licenses: GPL 3
Build system: r
Synopsis: Functions for Working with Danish CPR Numbers
Description:

Calculate date of birth, age, and gender, and generate anonymous sequence numbers from CPR numbers. <https://en.wikipedia.org/wiki/Personal_identification_number_(Denmark)>.

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Total results: 68655