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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-usdampr 1.0.1
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://github.com/cbw1243/usdampr
Licenses: GPL 2+
Build system: r
Synopsis: Request USDA MPR Historical Data via the 'LMR' API
Description:

Interface to easily access data via the United States Department of Agriculture (USDA)'s Livestock Mandatory Reporting ('LMR') Data API at <https://mpr.datamart.ams.usda.gov/>. The downloaded data can be saved for later off-line use. Also provide relevant information and metadata for each of the input variables needed for sending the data inquiry.

r-unilasso 2.11
Propagated dependencies: r-mass@7.3-65 r-glmnet@4.1-10
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://cran.r-project.org/package=uniLasso
Licenses: GPL 2
Build system: r
Synopsis: Univariate-Guided Sparse Regression
Description:

Fit a univariate-guided sparse regression (lasso), by a two-stage procedure. The first stage fits p separate univariate models to the response. The second stage gives more weight to the more important univariate features, and preserves their signs. Conveniently, it returns an objects that inherits from class glmnet', so that all of the methods for glmnet are available. See Chatterjee, Hastie and Tibshirani (2025) <doi:10.1162/99608f92.c79ff6db> for details.

r-upndown 0.3.0
Propagated dependencies: r-plyr@1.8.9 r-mass@7.3-65 r-expm@1.0-0 r-cir@2.5.1
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://cran.r-project.org/package=upndown
Licenses: GPL 2
Build system: r
Synopsis: Utilities and Design Aids for Up-and-Down Dose-Finding Studies
Description:

Up-and-Down (UD) is the most popular design approach for dose-finding, but it has been severely under-served by the statistical and computing communities. This is the first package that comprehensively addresses UD's needs. Recent applied UD tutorial: Oron et al., 2022 <doi:10.1097/ALN.0000000000004282>. Recent methodological overview: Oron and Flournoy, 2024 <doi:10.51387/24-NEJSDS74>.

r-upset-hp 0.0.5
Propagated dependencies: r-vegan@2.7-2 r-patchwork@1.3.2 r-mumin@1.48.11 r-glmm-hp@1.0-0 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://github.com/laijiangshan/upset.hp
Licenses: GPL 2+
Build system: r
Synopsis: Generate UpSet Plots of VP and HP Based on the ASV Concept
Description:

Using matrix layout to visualize the unique, common, or individual contribution of each predictor (or matrix of predictors) towards explained variation on different models. These contributions were derived from variation partitioning (VP) and hierarchical partitioning (HP), applying the algorithm of "Lai et al. (2022) Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package.Methods in Ecology and Evolution, 13: 782-788 <doi:10.1111/2041-210X.13800>".

r-ugarima 0.1.0
Propagated dependencies: r-lamw@2.2.5
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://cran.r-project.org/package=UGarima
Licenses: GPL 3
Build system: r
Synopsis: The Unit-Garima Distribution
Description:

Density, distribution function, quantile function, and random generating function of the Unit-Garima distribution based on Ayuyuen, S., & Bodhisuwan, W. (2024)<doi:10.18187/pjsor.v20i1.4307>.

r-uahdatasciencesf 1.0.0
Propagated dependencies: r-magick@2.9.0 r-crayon@1.5.3
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://cran.r-project.org/package=UAHDataScienceSF
Licenses: Expat
Build system: r
Synopsis: Interactive Statistical Learning Functions
Description:

An educational toolkit for learning statistical concepts through interactive exploration. Provides functions for basic statistics (mean, variance, etc.) and probability distributions with step-by-step explanations and interactive learning modes. Each function can be used for simple calculations, detailed learning with explanations, or interactive practice with feedback.

r-ubair 1.1.1
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://gitlab.opencode.de/uba-ki-lab/ubair
Licenses: GPL 3+
Build system: r
Synopsis: Effects of External Conditions on Air Quality
Description:

Analyzes the impact of external conditions on air quality using counterfactual approaches, featuring methods for data preparation, modeling, and visualization.

r-unival 1.1.0
Propagated dependencies: r-psych@2.5.6
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://cran.r-project.org/package=unival
Licenses: GPL 3
Build system: r
Synopsis: Assessing Essential Unidimensionality Using External Validity Information
Description:

Assess essential unidimensionality using external validity information using the procedure proposed by Ferrando & Lorenzo-Seva (2019) <doi:10.1177/0013164418824755>. Provides two indices for assessing differential and incremental validity, both based on a second-order modelling schema for the general factor.

r-uclust 1.0.0
Propagated dependencies: r-robcor@0.1-6.1 r-dendextend@1.19.1
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://cran.r-project.org/package=uclust
Licenses: GPL 3
Build system: r
Synopsis: Clustering and Classification Inference with U-Statistics
Description:

Clustering and classification inference for high dimension low sample size (HDLSS) data with U-statistics. The package contains implementations of nonparametric statistical tests for sample homogeneity, group separation, clustering, and classification of multivariate data. The methods have high statistical power and are tailored for data in which the dimension L is much larger than sample size n. See Gabriela B. Cybis, Marcio Valk and SÃ lvia RC Lopes (2018) <doi:10.1080/00949655.2017.1374387>, Marcio Valk and Gabriela B. Cybis (2020) <doi:10.1080/10618600.2020.1796398>, Debora Z. Bello, Marcio Valk and Gabriela B. Cybis (2021) <arXiv:2106.09115>.

r-uotm 0.1.6
Propagated dependencies: r-hash@2.2.6.3 r-ggplot2@4.0.1 r-forecast@8.24.0 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://cran.r-project.org/package=uotm
Licenses: GPL 3
Build system: r
Synopsis: Uncertainty of Time Series Model Selection Methods
Description:

We propose a new procedure, called model uncertainty variance, which can quantify the uncertainty of model selection on Autoregressive Moving Average models. The model uncertainty variance not pay attention to the accuracy of prediction, but focus on model selection uncertainty and providing more information of the model selection results. And to estimate the model measures, we propose an simplify and faster algorithm based on bootstrap method, which is proven to be effective and feasible by Monte-Carlo simulation. At the same time, we also made some optimizations and adjustments to the Model Confidence Bounds algorithm, so that it can be applied to the time series model selection method. The consistency of the algorithm result is also verified by Monte-Carlo simulation. We propose a new procedure, called model uncertainty variance, which can quantify the uncertainty of model selection on Autoregressive Moving Average models. The model uncertainty variance focuses on model selection uncertainty and providing more information of the model selection results. To estimate the model uncertainty variance, we propose an simplified and faster algorithm based on bootstrap method, which is proven to be effective and feasible by Monte-Carlo simulation. At the same time, we also made some optimizations and adjustments to the Model Confidence Bounds algorithm, so that it can be applied to the time series model selection method. The consistency of the algorithm result is also verified by Monte-Carlo simulation. Please see Li,Y., Luo,Y., Ferrari,D., Hu,X. and Qin,Y. (2019) Model Confidence Bounds for Variable Selection. Biometrics, 75:392-403.<DOI:10.1111/biom.13024> for more information.

r-usmap 1.0.0
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://usmap.dev
Licenses: GPL 3+
Build system: r
Synopsis: US Maps Including Alaska and Hawaii
Description:

Obtain United States map data frames of varying region types (e.g. county, state). The map data frames include Alaska and Hawaii conveniently placed to the bottom left, as they appear in most maps of the US. Convenience functions for plotting choropleths, visualizing spatial data, and working with FIPS codes are also provided.

r-upcm 0.0-5
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://cran.r-project.org/package=UPCM
Licenses: GPL 2+
Build system: r
Synopsis: Uncertainty in Partial Credit Models
Description:

This package provides an extension to the Partial Credit Model and Generalized Partial Credit Models which allows for an additional person parameter that characterizes the uncertainty of the person. The method was originally proposed by Tutz and Schauberger (2020) <doi:10.1177/0146621620920932>.

r-unifdag 1.0.4
Propagated dependencies: r-graph@1.88.0 r-gmp@0.7-5
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://cran.r-project.org/package=unifDAG
Licenses: GPL 2+
Build system: r
Synopsis: Uniform Sampling of Directed Acyclic Graphs
Description:

Uniform sampling of Directed Acyclic Graphs (DAG) using exact enumeration by relating each DAG to a sequence of outpoints (nodes with no incoming edges) and then to a composition of integers as suggested by Kuipers, J. and Moffa, G. (2015) <doi:10.1007/s11222-013-9428-y>.

r-usdm 2.1-7
Propagated dependencies: r-terra@1.8-86 r-raster@3.6-32
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://r-gis.net/
Licenses: GPL 3+
Build system: r
Synopsis: Uncertainty Analysis for Species Distribution Models
Description:

This is a framework that aims to provide methods and tools for assessing the impact of different sources of uncertainties (e.g.positional uncertainty) on performance of species distribution models (SDMs).).

r-unisensr 0.3.4
Propagated dependencies: r-xml@3.99-0.20 r-vroom@1.6.6 r-hexview@0.3-4
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://unisens.org/
Licenses: LGPL 2.0+
Build system: r
Synopsis: Read 'Unisens' Data
Description:

This package provides the ability to read Unisens data into R. Unisens is a universal data format for multi sensor data.

r-uptimerobot 1.0.0
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://gabrielebaldassarre.com/r/uptimerobot
Licenses: Expat
Build system: r
Synopsis: Access the UptimeRobot Ping API
Description:

Provide a set of wrappers to call all the endpoints of UptimeRobot API which includes various kind of ping, keep-alive and speed tests. See <https://uptimerobot.com/> for more information.

r-usefun 0.5.2
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://github.com/bblodfon/usefun
Licenses: Expat
Build system: r
Synopsis: Collection of Useful Functions by John
Description:

This package provides a set of general functions that I have used in various projects and other R packages. Miscellaneous operations on data frames, matrices and vectors, ROC and PR statistics.

r-unrepx 1.0-2
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://cran.r-project.org/package=unrepx
Licenses: GPL 2+
Build system: r
Synopsis: Analysis and Graphics for Unreplicated Experiments
Description:

This package provides half-normal plots, reference plots, and Pareto plots of effects from an unreplicated experiment, along with various pseudo-standard-error measures, simulated reference distributions, and other tools. Many of these methods are described in Daniel C. (1959) <doi:10.1080/00401706.1959.10489866> and/or Lenth R.V. (1989) <doi:10.1080/00401706.1989.10488595>, but some new approaches are added and integrated in one package.

r-unico 0.1.0
Propagated dependencies: r-testit@0.13 r-pracma@2.4.6 r-pbapply@1.7-4 r-nloptr@2.2.1 r-mgcv@1.9-4 r-matrixstats@1.5.0 r-matrixcalc@1.0-6 r-mass@7.3-65 r-futile-logger@1.4.3 r-data-table@1.17.8 r-config@0.3.2 r-compositions@2.0-9
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://cozygene.github.io/Unico/
Licenses: GPL 3
Build system: r
Synopsis: Unified Cross-Omics Deconvolution
Description:

UNIfied Cross-Omics deconvolution (Unico) deconvolves standard 2-dimensional bulk matrices of samples by features into a 3-dimensional tensors representing samples by features by cell types. Unico stands out as the first principled model-based deconvolution method that is theoretically justified for any heterogeneous genomic data. For more details see Chen and Rahmani et al. (2024) <doi:10.1101/2024.01.27.577588>.

r-ukfe 2.0.0
Propagated dependencies: r-xml2@1.5.0 r-sf@1.0-23
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://cran.r-project.org/package=UKFE
Licenses: GPL 3
Build system: r
Synopsis: UK Flood Estimation
Description:

This package provides functions to implement the methods of the Flood Estimation Handbook (FEH), associated updates and the revitalised flood hydrograph model (ReFH). Currently the package uses NRFA peak flow dataset version 14. Aside from FEH functionality, further hydrological functions are available. Most of the methods implemented in this package are described in one or more of the following: "Flood Estimation Handbook", Centre for Ecology & Hydrology (1999, ISBN:0 948540 94 X). "Flood Estimation Handbook Supplementary Report No. 1", Kjeldsen (2007, ISBN:0 903741 15 7). "Regional Frequency Analysis - an approach based on L-moments", Hosking & Wallis (1997, ISBN: 978 0 521 01940 8). "Making better use of local data in flood frequency estimation", Environment Agency (2017, ISBN: 978 1 84911 387 8). "Sampling uncertainty of UK design flood estimation" , Hammond (2021, <doi:10.2166/nh.2021.059>). "The FEH 2025 statistical method update", UK Centre for Ecology and Hydrology (2025). "Low flow estimation in the United Kingdom", Institute of Hydrology (1992, ISBN 0 948540 45 1). Data from the UK National River Flow Archive (<https://nrfa.ceh.ac.uk/>, terms and conditions: <https://nrfa.ceh.ac.uk/help/costs-terms-and-conditions>).

r-usgrid 0.1.2
Propagated dependencies: r-tsibble@1.2.0
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://github.com/RamiKrispin/USgrid
Licenses: Expat
Build system: r
Synopsis: The Demand and Supply for Electricity in the US
Description:

This package provides a set of regular time-series datasets, describing the US electricity grid. That includes the total demand and supply, and as well as the demand by energy source (coal, solar, wind, etc.). Source: US Energy Information Administration (Dec 2019) <https://www.eia.gov/>.

r-usemodels 0.2.0
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://usemodels.tidymodels.org/
Licenses: Expat
Build system: r
Synopsis: Boilerplate Code for 'Tidymodels' Analyses
Description:

Code snippets to fit models using the tidymodels framework can be easily created for a given data set.

r-urlshortener 2.0.0
Propagated dependencies: r-stringr@1.6.0 r-shiny@1.11.1 r-miniui@0.1.2 r-lubridate@1.9.4 r-jsonlite@2.0.0 r-httr2@1.2.1 r-clipr@0.8.0 r-cli@3.6.5 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://github.com/dmpe/urlshorteneR
Licenses: ASL 2.0
Build system: r
Synopsis: R Wrapper for the 'Bit.ly' and 'Is.gd'/'v.gd' URL Shortening Services
Description:

Allows using two URL shortening services, which also provide expanding and analytic functions. Specifically developed for Bit.ly (which requires OAuth 2.0) and is.gd (no API key).

r-updog 2.1.6
Channel: guix-cran
Location: guix-cran/packages/u.scm (guix-cran packages u)
Home page: https://dcgerard.github.io/updog/
Licenses: GPL 3+
Build system: r
Synopsis: Flexible Genotyping for Polyploids
Description:

This package implements empirical Bayes approaches to genotype polyploids from next generation sequencing data while accounting for allele bias, overdispersion, and sequencing error. The main functions are flexdog() and multidog(), which allow the specification of many different genotype distributions. Also provided are functions to simulate genotypes, rgeno(), and read-counts, rflexdog(), as well as functions to calculate oracle genotyping error rates, oracle_mis(), and correlation with the true genotypes, oracle_cor(). These latter two functions are useful for read depth calculations. Run browseVignettes(package = "updog") in R for example usage. See Gerard et al. (2018) <doi:10.1534/genetics.118.301468> and Gerard and Ferrao (2020) <doi:10.1093/bioinformatics/btz852> for details on the implemented methods.

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Total results: 69112