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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-ohdsishinyappbuilder 1.0.0
Propagated dependencies: r-shinydashboard@0.7.3 r-shiny@1.11.1 r-rlang@1.1.6 r-resultmodelmanager@0.6.2 r-parallellogger@3.5.1 r-dplyr@1.1.4 r-devtools@2.4.6 r-databaseconnector@7.1.0 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=OhdsiShinyAppBuilder
Licenses: ASL 2.0
Build system: r
Synopsis: Viewing Observational Health Data Sciences and Informatics Results via 'shiny' Modules
Description:

Users can build a single shiny app for exploring population characterization, population-level causal effect estimation, and patient-level prediction results generated via the R analyses packages in HADES (see <https://ohdsi.github.io/Hades/>). Learn more about OhdsiShinyAppBuilder at <https://ohdsi.github.io/OhdsiShinyAppBuilder/>.

r-oknne 1.0.1
Propagated dependencies: r-fnn@1.1.4.1
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=OkNNE
Licenses: GPL 3+
Build system: r
Synopsis: k-Nearest Neighbours Ensemble via Optimal Model Selection for Regression
Description:

Optimal k Nearest Neighbours Ensemble is an ensemble of base k nearest neighbour models each constructed on a bootstrap sample with a random subset of features. k closest observations are identified for a test point "x" (say), in each base k nearest neighbour model to fit a stepwise regression to predict the output value of "x". The final predicted value of "x" is the mean of estimates given by all the models. The implemented model takes training and test datasets and trains the model on training data to predict the test data. Ali, A., Hamraz, M., Kumam, P., Khan, D.M., Khalil, U., Sulaiman, M. and Khan, Z. (2020) <DOI:10.1109/ACCESS.2020.3010099>.

r-optcirclust 0.0.4
Propagated dependencies: r-reshape2@1.4.5 r-rdpack@2.6.4 r-rcpp@1.1.0 r-plotrix@3.8-13 r-ckmeans-1d-dp@4.3.5
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=OptCirClust
Licenses: LGPL 3+
Build system: r
Synopsis: Circular, Periodic, or Framed Data Clustering: Fast, Optimal, and Reproducible
Description:

Fast, optimal, and reproducible clustering algorithms for circular, periodic, or framed data. The algorithms introduced here are based on a core algorithm for optimal framed clustering the authors have developed (Debnath & Song 2021) <doi:10.1109/TCBB.2021.3077573>. The runtime of these algorithms is O(K N log^2 N), where K is the number of clusters and N is the number of circular data points. On a desktop computer using a single processor core, millions of data points can be grouped into a few clusters within seconds. One can apply the algorithms to characterize events along circular DNA molecules, circular RNA molecules, and circular genomes of bacteria, chloroplast, and mitochondria. One can also cluster climate data along any given longitude or latitude. Periodic data clustering can be formulated as circular clustering. The algorithms offer a general high-performance solution to circular, periodic, or framed data clustering.

r-orthopanels 1.2-4
Propagated dependencies: r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=OrthoPanels
Licenses: GPL 3+
Build system: r
Synopsis: Dynamic Panel Models with Orthogonal Reparameterization of Fixed Effects
Description:

This package implements the orthogonal reparameterization approach recommended by Lancaster (2002) to estimate dynamic panel models with fixed effects (and optionally: panel specific intercepts). The approach uses a likelihood-based estimator and produces estimates that are asymptotically unbiased as N goes to infinity, with a T as low as 2.

r-openappr 0.2.0
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-rsqlite@2.4.4 r-rpostgres@1.4.8 r-rlang@1.1.6 r-purrr@1.2.0 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-dplyr@1.1.4 r-dbi@1.2.3
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=openappr
Licenses: LGPL 3+
Build system: r
Synopsis: Retrieve App Data from 'OpenAppBuilder'
Description:

This package provides an interface to connect R with the <https://github.com/IDEMSInternational/open-app-builder> OpenAppBuilder platform, enabling users to retrieve and work with user and notification data for analysis and processing. It is designed for developers and analysts to seamlessly integrate data from OpenAppBuilder into R workflows via a Postgres database connection, allowing direct querying and import of app data into R.

r-odiffr 0.5.1
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://github.com/BenWolst/odiffr
Licenses: Expat
Build system: r
Synopsis: Fast Pixel-by-Pixel Image Comparison Using 'odiff'
Description:

R bindings to odiff', a blazing-fast pixel-by-pixel image comparison tool <https://github.com/dmtrKovalenko/odiff>. Supports PNG, JPEG, WEBP, and TIFF with configurable thresholds, antialiasing detection, and region ignoring. Requires system installation of odiff'. Ideal for visual regression testing in automated workflows.

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-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-oddstream 0.5.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-reshape@0.8.10 r-rcpproll@0.3.1 r-rcolorbrewer@1.1-3 r-pcapp@2.0-5 r-mvtsplot@1.0-5 r-moments@0.14.1 r-mgcv@1.9-4 r-mass@7.3-65 r-magrittr@2.0.4 r-ks@1.15.1 r-kernlab@0.9-33 r-ggplot2@4.0.1 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=oddstream
Licenses: GPL 3
Build system: r
Synopsis: Outlier Detection in Data Streams
Description:

We proposes a framework that provides real time support for early detection of anomalous series within a large collection of streaming time series data. By definition, anomalies are rare in comparison to a system's typical behaviour. We define an anomaly as an observation that is very unlikely given the forecast distribution. The algorithm first forecasts a boundary for the system's typical behaviour using a representative sample of the typical behaviour of the system. An approach based on extreme value theory is used for this boundary prediction process. Then a sliding window is used to test for anomalous series within the newly arrived collection of series. Feature based representation of time series is used as the input to the model. To cope with concept drift, the forecast boundary for the system's typical behaviour is updated periodically. More details regarding the algorithm can be found in Talagala, P. D., Hyndman, R. J., Smith-Miles, K., et al. (2019) <doi:10.1080/10618600.2019.1617160>.

r-outreg 0.2.2
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-sandwich@3.1-1 r-reshape2@1.4.5 r-magrittr@2.0.4
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://github.com/kota7/outreg
Licenses: Expat
Build system: r
Synopsis: Regression Table for Publication
Description:

Create regression tables for publication. Currently supports lm', glm', survreg', and ivreg outputs.

r-optic 1.0.1
Propagated dependencies: r-tidyr@1.3.1 r-sandwich@3.1-1 r-rlang@1.1.6 r-r6@2.6.1 r-purrr@1.2.0 r-mass@7.3-65 r-magrittr@2.0.4 r-lmtest@0.9-40 r-future-apply@1.20.0 r-dplyr@1.1.4 r-did@2.3.0
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://randcorporation.github.io/optic/
Licenses: GPL 3
Build system: r
Synopsis: Simulation Tool for Causal Inference Using Longitudinal Data
Description:

This package implements a simulation study to assess the strengths and weaknesses of causal inference methods for estimating policy effects using panel data. See Griffin et al. (2021) <doi:10.1007/s10742-022-00284-w> and Griffin et al. (2022) <doi:10.1186/s12874-021-01471-y> for a description of our methods.

r-onearm2stage 1.2.1
Propagated dependencies: r-survival@3.8-3 r-ipdfromkm@0.1.10 r-flexsurv@2.3.2
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=OneArm2stage
Licenses: GPL 3+
Build system: r
Synopsis: Phase II Single-Arm Two-Stage Designs with Time-to-Event Outcomes
Description:

Two-stage design for single-arm phase II trials with time-to-event endpoints (e.g., clinical trials on immunotherapies among cancer patients) can be calculated using this package. Two notable advantages of the package: 1) It provides flexible choices from three design methods (optimal, minmax, and admissible), and 2) the power of the design is more accurately calculated using the exact variance in the one-sample log-rank test. The package can be used for 1) planning the sample sizes and other design parameters, and 2) conducting the interim and final analyses for the Go/No-go decisions. More details about the design method can be found in: Wu, J, Chen L, Wei J, Weiss H, Chauhan A. (2020). <doi:10.1002/pst.1983>.

r-opencl 0.2-11
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://www.rforge.net/OpenCL/
Licenses: Modified BSD
Build system: r
Synopsis: Interface allowing R to use OpenCL
Description:

This package provides an interface to OpenCL, allowing R to leverage computing power of GPUs and other HPC accelerator devices.

r-opimputation 0.6
Propagated dependencies: r-twosamples@2.0.1 r-rfit@0.27.0 r-reshape2@1.4.5 r-progressr@0.18.0 r-multius@1.2.3 r-missforest@1.6.1 r-miceranger@1.5.0 r-mice@3.18.0 r-mi@1.2 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-ggh4x@0.3.1 r-future-apply@1.20.0 r-future@1.68.0 r-datavisualizations@1.4.0 r-cowplot@1.2.0 r-caret@7.0-1 r-amelia@1.8.3 r-abind@1.4-8 r-abcanalysis@1.2.1
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://github.com/JornLotsch/opImputation
Licenses: GPL 3
Build system: r
Synopsis: Optimal Selection of Imputation Methods for Pain-Related Numerical Data
Description:

This package provides a model-agnostic framework for selecting dataset-specific imputation methods for missing values in numerical data related to pain. Lotsch J, Ultsch A (2025) "A model-agnostic framework for dataset-specific selection of missing value imputation methods in pain-related numerical data" Canadian Journal of Pain (in minor revision).

r-orthodr 0.6.8
Propagated dependencies: r-survival@3.8-3 r-rgl@1.3.31 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-pracma@2.4.6 r-plot3d@1.4.2 r-mass@7.3-65 r-dr@3.0.11
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://github.com/teazrq/orthoDr
Licenses: GPL 2+
Build system: r
Synopsis: Semi-Parametric Dimension Reduction Models Using Orthogonality Constrained Optimization
Description:

Utilize an orthogonality constrained optimization algorithm of Wen & Yin (2013) <DOI:10.1007/s10107-012-0584-1> to solve a variety of dimension reduction problems in the semiparametric framework, such as Ma & Zhu (2012) <DOI:10.1080/01621459.2011.646925>, Ma & Zhu (2013) <DOI:10.1214/12-AOS1072>, Sun, Zhu, Wang & Zeng (2019) <DOI:10.1093/biomet/asy064> and Zhou, Zhu & Zeng (2021) <DOI:10.1093/biomet/asaa087>. The package also implements some existing dimension reduction methods such as hMave by Xia, Zhang, & Xu (2010) <DOI:10.1198/jasa.2009.tm09372> and partial SAVE by Feng, Wen & Zhu (2013) <DOI:10.1080/01621459.2012.746065>. It also serves as a general purpose optimization solver for problems with orthogonality constraints, i.e., in Stiefel manifold. Parallel computing for approximating the gradient is enabled through OpenMP'.

r-olympicrshiny 1.0.2
Propagated dependencies: r-summarytools@1.1.4 r-shinythemes@1.2.0 r-shinybusy@0.3.3 r-shiny@1.11.1 r-golem@0.5.1 r-ggplot2@4.0.1 r-forcats@1.0.1 r-dplyr@1.1.4 r-config@0.3.2
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://github.com/Amalan-ConStat/OlympicRshiny
Licenses: Expat
Build system: r
Synopsis: 'Shiny' Application for Olympic Data
Description:

Shiny Application to visualize Olympic Data. From 1896 to 2016. Even Winter Olympics events are included. Data is from Kaggle at <https://www.kaggle.com/heesoo37/120-years-of-olympic-history-athletes-and-results>.

r-o2ools 0.0.1
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://github.com/CyGei/o2ools
Licenses: Expat
Build system: r
Synopsis: Tools for 'outbreaker2'
Description:

Streamlines the post-processing, summarization, and visualization of outbreaker2 output via a suite of helper functions. Facilitates tidy manipulation of posterior samples, integration with case metadata, generation of diagnostic plots and summary statistics.

r-oottest 0.9.1
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://github.com/PhilippKuelpmann/oottest
Licenses: Expat
Build system: r
Synopsis: Out-of-Treatment Testing
Description:

This package implements the out-of-treatment testing from Kuelpmann and Kuzmics (2020) <doi:10.2139/ssrn.3441675> based on the Vuong Test introduced in Vuong (1989) <doi:10.2307/1912557>. Out-of treatment testing allows for a direct, pairwise likelihood comparison of theories, calibrated with pre-existing data.

r-optistock 0.0.2
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=optistock
Licenses: Expat
Build system: r
Synopsis: Determine Optimum Stocking Times Used in Fishery Enhancements
Description:

This package provides a collection of functions that aid in calculating the optimum time to stock hatchery reared fish into a body of water given the growth, mortality and cost of raising a particular number of individuals to a certain length.

r-once 0.4.1
Propagated dependencies: r-magrittr@2.0.4
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://gdmcdonald.github.io/once/
Licenses: Expat
Build system: r
Synopsis: Execute Expensive Operations Only Once
Description:

Allows you to easily execute expensive compute operations only once, and save the resulting object to disk.

r-optrefine 1.1.1
Propagated dependencies: r-sampling@2.11 r-rglpk@0.6-5.1 r-mass@7.3-65 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://github.com/kkbrum/optrefine
Licenses: GPL 3+
Build system: r
Synopsis: Optimally Refine Strata
Description:

Splits initial strata into refined strata that optimize covariate balance. For more information, please see Brumberg, Small, and Rosenbaum (2024) <doi:10.1093/biomtc/ujae061>. To solve the linear program, the Gurobi commercial optimization software is recommended, but not required. The gurobi R package can be installed following the instructions at <https://docs.gurobi.com/projects/optimizer/en/current/reference/r/setup.html> after claiming your free academic license at <https://www.gurobi.com/academia/academic-program-and-licenses/>.

r-okcolors 0.1.0
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/nelsonquesado/okcolors
Licenses: GPL 3
Build system: r
Synopsis: Set of Color Palettes Inspired by OK Go Music Videos for 'ggplot2' in R
Description:

This package provides a collection of aesthetically appealing color palettes for effective data visualization with ggplot2'. Palettes support both discrete and continuous data.

r-optimmodel 2.0-3
Propagated dependencies: r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=OptimModel
Licenses: GPL 2
Build system: r
Synopsis: Perform Nonlinear Regression Using 'optim' as the Optimization Engine
Description:

This package provides a wrapper for optim for nonlinear regression problems; see Nocedal J and Write S (2006, ISBN: 978-0387-30303-1). Performs ordinary least squares (OLS), iterative re-weighted least squares (IRWLS), and maximum likelihood (MLE). Also includes the robust outlier detection (ROUT) algorithm; see Motulsky, H and Brown, R (2006) <doi:10.1186/1471-2105-7-123>.

r-optimsimplex 1.0-8
Propagated dependencies: r-optimbase@1.0-10
Channel: guix-cran
Location: guix-cran/packages/o.scm (guix-cran packages o)
Home page: https://cran.r-project.org/package=optimsimplex
Licenses: FSDG-compatible
Build system: r
Synopsis: R Port of the 'Scilab' Optimsimplex Module
Description:

This package provides a building block for optimization algorithms based on a simplex. The optimsimplex package may be used in the following optimization methods: the simplex method of Spendley et al. (1962) <doi:10.1080/00401706.1962.10490033>, the method of Nelder and Mead (1965) <doi:10.1093/comjnl/7.4.308>, Box's algorithm for constrained optimization (1965) <doi:10.1093/comjnl/8.1.42>, the multi-dimensional search by Torczon (1989) <https://www.cs.wm.edu/~va/research/thesis.pdf>, etc...

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