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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-ofpetrial 0.1.3
Propagated dependencies: r-zip@2.3.3 r-tmap@4.2 r-tidyr@1.3.1 r-tibble@3.3.0 r-terra@1.8-86 r-sf@1.0-23 r-rmarkdown@2.30 r-purrr@1.2.0 r-magrittr@2.0.4 r-lwgeom@0.2-14 r-leaflet@2.2.3 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-ggextra@0.11.0 r-dplyr@1.1.4 r-data-table@1.17.8 r-bookdown@0.45
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://difm-brain.github.io/ofpetrial/
Licenses: GPL 3+
Build system: r
Synopsis: Design on-Farm Precision Field Agronomic Trials
Description:

This package provides a comprehensive system for designing and implementing on-farm precision field agronomic trials. You provide field data, tell ofpetrial how to design a trial, and get readily-usable trial design files and a report checks the validity and reliability of the trial design.

r-osnmtf 0.1.0
Propagated dependencies: r-mass@7.3-65 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=OSNMTF
Licenses: GPL 2+
Build system: r
Synopsis: Orthogonal Sparse Non-Negative Matrix Tri-Factorization
Description:

This package provides a novel method to implement cancer subtyping and subtype specific drug targets identification via non-negative matrix tri-factorization. To improve the interpretability, we introduce orthogonal constraint to the row coefficient matrix and column coefficient matrix. To meet the prior knowledge that each subtype should be strongly associated with few gene sets, we introduce sparsity constraint to the association sub-matrix. The average residue was introduced to evaluate the row and column cluster numbers. This is part of the work "Liver Cancer Analysis via Orthogonal Sparse Non-Negative Matrix Tri- Factorization" which will be submitted to BBRC.

r-overturer 0.2.5
Propagated dependencies: r-sf@1.0-23 r-rlang@1.1.6 r-glue@1.8.0 r-duckdb@1.4.2 r-dplyr@1.1.4 r-dbplyr@2.5.1 r-dbi@1.2.3
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://github.com/arthurgailes/overtureR
Licenses: Expat
Build system: r
Synopsis: Load 'Overture' Datasets as 'dbplyr' and 'sf'-Ready Data Frames
Description:

An integrated R interface to the Overture API (<https://docs.overturemaps.org/>). Allows R users to return Overture data as dbplyr data frames or materialized sf spatial data frames.

r-osdesign 1.8
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=osDesign
Licenses: GPL 3+
Build system: r
Synopsis: Design, Planning and Analysis of Observational Studies
Description:

This package provides a suite of functions for the design of case-control and two-phase studies, and the analysis of data that arise from them. Functions in this packages provides Monte Carlo based evaluation of operating characteristics such as powers for estimators of the components of a logistic regression model. For additional detail see: Haneuse S, Saegusa T and Lumley T (2011)<doi:10.18637/jss.v043.i11>.

r-ovtool 1.0.3
Propagated dependencies: r-varhandle@2.0.6 r-twang@2.6.2 r-tidyselect@1.2.1 r-tibble@3.3.0 r-survey@4.4-8 r-rlang@1.1.6 r-purrr@1.2.0 r-progress@1.2.3 r-metr@0.18.3 r-magrittr@2.0.4 r-glue@1.8.0 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-envstats@3.1.0 r-dplyr@1.1.4 r-devtools@2.4.6 r-amelia@1.8.3
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=OVtool
Licenses: GPL 3
Build system: r
Synopsis: Omitted Variable Tool
Description:

This tool was designed to assess the sensitivity of research findings to omitted variables when estimating causal effects using propensity score (PS) weighting. This tool produces graphics and summary results that will enable a researcher to quantify the impact an omitted variable would have on their results. Burgette et al. (2021) describe the methodology behind the primary function in this package, ov_sim. The method is demonstrated in Griffin et al. (2020) <doi:10.1016/j.jsat.2020.108075>.

r-oscillatorgenerator 0.1.0
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=OscillatorGenerator
Licenses: GPL 3+
Build system: r
Synopsis: Generation of Customizable, Discretized Time Series of Oscillating Species
Description:

The supplied code allows for the generation of discrete time series of oscillating species. General shapes can be selected by means of individual functions, which are widely customizable by means of function arguments. All code was developed in the Biological Information Processing Group at the BioQuant Center at Heidelberg University, Germany.

r-oosse 1.0.11
Propagated dependencies: r-rdpack@2.6.4 r-matrix@1.7-4 r-doparallel@1.0.17 r-biocparallel@1.44.0
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=oosse
Licenses: GPL 2
Build system: r
Synopsis: Out-of-Sample R² with Standard Error Estimation
Description:

Estimates out-of-sample R² through bootstrap or cross-validation as a measure of predictive performance. In addition, a standard error for this point estimate is provided, and confidence intervals are constructed.

r-ontologyplot 1.7
Propagated dependencies: r-rgraphviz@2.54.0 r-paintmap@1.0 r-ontologyindex@2.12
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=ontologyPlot
Licenses: GPL 2+
Build system: r
Synopsis: Visualising Sets of Ontological Terms
Description:

Create R plots visualising ontological terms and the relationships between them with various graphical options - Greene et al. 2017 <doi:10.1093/bioinformatics/btw763>.

r-oews2021 1.0.0
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=oews2021
Licenses: Expat
Build system: r
Synopsis: May 2021 Occupational Employment and Wage Statistics
Description:

This package contains data from the May 2021 Occupational Employment and Wage Statistics data release from the U.S. Bureau of Labor Statistics. The dataset covers employment and wages across occupations, industries, states, and at the national level. Metropolitan data is not included.

r-oclust 1.0.0
Propagated dependencies: r-progress@1.2.3 r-mvtnorm@1.3-3 r-mixture@2.2.0 r-mclust@6.1.2 r-mass@7.3-65 r-entropy@1.3.2 r-dbscan@1.2.3
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=oclust
Licenses: GPL 2+
Build system: r
Synopsis: Gaussian Model-Based Clustering with Outliers
Description:

This package provides a function to detect and trim outliers in Gaussian mixture model-based clustering using methods described in Clark and McNicholas (2024) <doi:10.1007/s00357-024-09473-3>.

r-ocd 1.1
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=ocd
Licenses: GPL 3
Build system: r
Synopsis: High-Dimensional Multiscale Online Changepoint Detection
Description:

This package implements the algorithm in Chen, Wang and Samworth (2020) <arxiv:2003.03668> for online detection of sudden mean changes in a sequence of high-dimensional observations. It also implements methods by Mei (2010) <doi:10.1093/biomet/asq010>, Xie and Siegmund (2013) <doi:10.1214/13-AOS1094> and Chan (2017) <doi:10.1214/17-AOS1546>.

r-observation 0.3.0
Propagated dependencies: r-svdialogs@1.1.1
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://github.com/paulhibbing/Observation
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Collect and Process Physical Activity Direct Observation Data
Description:

Two-part system for first collecting then managing direct observation data, as described by Hibbing PR, Ellingson LD, Dixon PM, & Welk GJ (2018) <doi:10.1249/MSS.0000000000001486>.

r-oddnet 0.1.1
Propagated dependencies: r-tsibble@1.1.6 r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-pcapp@2.0-5 r-lookout@2.0.0 r-igraph@2.2.1 r-fabletools@0.5.1 r-fable@0.5.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://sevvandi.github.io/oddnet/
Licenses: GPL 3+
Build system: r
Synopsis: Anomaly Detection in Temporal Networks
Description:

Anomaly detection in dynamic, temporal networks. The package oddnet uses a feature-based method to identify anomalies. First, it computes many features for each network. Then it models the features using time series methods. Using time series residuals it detects anomalies. This way, the temporal dependencies are accounted for when identifying anomalies (Kandanaarachchi, Hyndman 2022) <arXiv:2210.07407>.

r-obliquersf 0.1.2
Propagated dependencies: r-tidyr@1.3.1 r-survival@3.8-3 r-scales@1.4.0 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-purrr@1.2.0 r-prodlim@2025.04.28 r-pec@2025.06.24 r-missforest@1.6.1 r-glmnet@4.1-10 r-ggthemes@5.1.0 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=obliqueRSF
Licenses: GPL 3
Build system: r
Synopsis: Oblique Random Forests for Right-Censored Time-to-Event Data
Description:

Oblique random survival forests incorporate linear combinations of input variables into random survival forests (Ishwaran, 2008 <DOI:10.1214/08-AOAS169>). Regularized Cox proportional hazard models (Simon, 2016 <DOI:10.18637/jss.v039.i05>) are used to identify optimal linear combinations of input variables.

r-osmclass 0.1.3
Propagated dependencies: r-stringi@1.8.7 r-data-table@1.17.8 r-collapse@2.1.5
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=osmclass
Licenses: GPL 3
Build system: r
Synopsis: Classify Open Street Map Features
Description:

Classify Open Street Map (OSM) features into meaningful functional or analytical categories. Designed for OSM PBF files, e.g. from <https://download.geofabrik.de/> imported as spatial data frames. A classification consists of a list of categories that are related to certain OSM tags and values. Given a layer from an OSM PBF file and a classification, the main osm_classify() function returns a classification data table giving, for each feature, the primary and alternative categories (if there is overlap) assigned, and the tag(s) and value(s) matched on. The package also contains a classification of OSM features by economic function/significance, following Krantz (2023) <https://www.ssrn.com/abstract=4537867>.

r-optconerrf 1.0.1
Propagated dependencies: r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://github.com/morten-dreher/optconerrf
Licenses: GPL 3+
Build system: r
Synopsis: Optimal Monotone Conditional Error Functions
Description:

Design and analysis of confirmatory adaptive clinical trials using the optimal conditional error framework according to Brannath and Bauer (2004) <doi:10.1111/j.0006-341X.2004.00221.x>. An extension to the optimal conditional error function using interim estimates as described in Brannath and Dreher (2024) <doi:10.48550/arXiv.2402.00814> and functions to ensure that the resulting conditional error function is non-increasing are also available.

r-oneinfl 1.0.2
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=oneinfl
Licenses: GPL 3+
Build system: r
Synopsis: Estimates OIPP and OIZTNB Regression Models
Description:

Estimates one-inflated positive Poisson (OIPP) and one-inflated zero-truncated negative binomial (OIZTNB) regression models. A suite of ancillary statistical tools are also provided, including: estimation of positive Poisson (PP) and zero-truncated negative binomial (ZTNB) models; marginal effects and their standard errors; diagnostic likelihood ratio and Wald tests; plotting; predicted counts and expected responses; and random variate generation. The models and tools, as well as four applications, are shown in Godwin, R. T. (2024). "One-inflated zero-truncated count regression models" arXiv preprint <doi:10.48550/arXiv.2402.02272>.

r-osum 0.1.0
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://zivankaraman.github.io/osum/
Licenses: GPL 3
Build system: r
Synopsis: Provide Summary Information About R Objects
Description:

Inspired by S-PLUS function objects.summary(), provides a function with the same name that returns data class, storage mode, mode, type, dimension, and size information for R objects in the specified environment. Various filtering and sorting options are also proposed.

r-oc 1.2.1
Propagated dependencies: r-pscl@1.5.9
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://legacy.voteview.com/oc_in_R.htm
Licenses: GPL 2
Build system: r
Synopsis: Optimal Classification Roll Call Analysis Software
Description:

Estimates optimal classification (Poole 2000) <doi:10.1093/oxfordjournals.pan.a029814> scores from roll call votes supplied though a rollcall object from package pscl'.

r-orcidtr 0.1.0
Propagated dependencies: r-jsonlite@2.0.0 r-httr2@1.2.1 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://github.com/lorenzoFabbri/orcidtr
Licenses: Expat
Build system: r
Synopsis: Retrieve Data from the ORCID Public API
Description:

This package provides functions to retrieve public data from ORCID (Open Researcher and Contributor ID) records via the ORCID public API. Fetches employment history, education, works (publications, datasets, preprints), funding, peer review activities, and other public information. Returns data as structured data.table objects for easy analysis and manipulation. Replaces the discontinued rorcid package with a modern, CRAN-compliant implementation.

r-ollamar 1.2.2
Propagated dependencies: r-tibble@3.3.0 r-jsonlite@2.0.0 r-httr2@1.2.1 r-glue@1.8.0 r-crayon@1.5.3 r-base64enc@0.1-3
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://hauselin.github.io/ollama-r/
Licenses: Expat
Build system: r
Synopsis: 'Ollama' Language Models
Description:

An interface to easily run local language models with Ollama <https://ollama.com> server and API endpoints (see <https://github.com/ollama/ollama/blob/main/docs/api.md> for details). It lets you run open-source large language models locally on your machine.

r-oncmap 0.1.7
Propagated dependencies: r-zoo@1.8-14 r-readxl@1.4.5 r-readr@2.1.6 r-lubridate@1.9.4 r-hms@1.1.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=oncmap
Licenses: Expat
Build system: r
Synopsis: Analyze Data from Electronic Adherence Monitoring Devices
Description:

Medication adherence, defined as medication-taking behavior that aligns with the agreed-upon treatment protocol, is critical for realizing the benefits of prescription medications. Medication adherence can be assessed using electronic adherence monitoring devices (EAMDs), pill bottles or boxes that contain a computer chip that records the date and time of each opening (or â actuationâ ). Before researchers can use EAMD data, they must apply a series of decision rules to transform actuation data into adherence data. The purpose of this R package ('oncmap') is to transform EAMD actuations in the form of a raw .csv file, information about the patient, regimen, and non-monitored periods into two daily adherence values -- Dose Taken and Correct Dose Taken.

r-oceanis 1.8.5
Propagated dependencies: r-zip@2.3.3 r-webshot@0.5.5 r-stringr@1.6.0 r-shinythemes@1.2.0 r-shinyjs@2.1.0 r-shinybs@0.61.1 r-shiny@1.11.1 r-sf@1.0-23 r-lwgeom@0.2-14 r-leaflet-extras@2.0.1 r-leaflet@2.2.3 r-htmlwidgets@1.6.4 r-ggplot2@4.0.1 r-dt@0.34.0 r-dplyr@1.1.4 r-classint@0.4-11
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://github.com/insee-psar-at/oceanis-package/
Licenses: GPL 2+ FSDG-compatible
Build system: r
Synopsis: Cartography for Statistical Analysis
Description:

Creating maps for statistical analysis such as proportional circles, choropleth, typology and flows. Some functions use shiny or leaflet technologies for dynamism and interactivity. The great features are : - Create maps in a web environment where the parameters are modifiable on the fly ('shiny and leaflet technologies). - Create interactive maps through zoom and pop-up ('leaflet technology). - Create frozen maps with the possibility to add labels.

r-olcpm 0.1.2
Propagated dependencies: r-rspectra@0.16-2 r-laplacesdemon@16.1.6
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=OLCPM
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Online Change Point Detection for Matrix-Valued Time Series
Description:

We provide two algorithms for monitoring change points with online matrix-valued time series, under the assumption of a two-way factor structure. The algorithms are based on different calculations of the second moment matrices. One is based on stacking the columns of matrix observations, while another is by a more delicate projected approach. A well-known fact is that, in the presence of a change point, a factor model can be rewritten as a model with a larger number of common factors. In turn, this entails that, in the presence of a change point, the number of spiked eigenvalues in the second moment matrix of the data increases. Based on this, we propose two families of procedures - one based on the fluctuations of partial sums, and one based on extreme value theory - to monitor whether the first non-spiked eigenvalue diverges after a point in time in the monitoring horizon, thereby indicating the presence of a change point. This package also provides some simple functions for detecting and removing outliers, imputing missing entries and testing moments. See more details in He et al. (2021)<doi:10.48550/arXiv.2112.13479>.

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