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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-rdp 0.3.0
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/robertdj/RDP
Licenses: GPL 3
Build system: r
Synopsis: The Ramer-Douglas-Peucker Algorithm
Description:

Pretty fast implementation of the Ramer-Douglas-Peucker algorithm for reducing the number of points on a 2D curve. Urs Ramer (1972), "An iterative procedure for the polygonal approximation of plane curves" <doi:10.1016/S0146-664X(72)80017-0>. David H. Douglas and Thomas K. Peucker (1973), "Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or its Caricature" <doi:10.3138/FM57-6770-U75U-7727>.

r-rsstest 1.0
Propagated dependencies: r-huxtable@5.8.0
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://cran.r-project.org/package=RSStest
Licenses: GPL 2
Build system: r
Synopsis: Testing the Equality of Two Means Using RSS and MRSS
Description:

Testing the equality of two means using Ranked Set Sampling and Median Ranked Set Sampling are provided under normal distribution. Data generation functions are also given RSS and MRSS. Also, data generation functions are given under imperfect ranking data for Ranked Set Sampling and Median Ranked Set Sampling. Ozdemir Y.A., Ebegil M., & Gokpinar F. (2019), <doi:10.1007/s40995-018-0558-0> Ozdemir Y.A., Ebegil M., & Gokpinar F. (2017), <doi:10.1080/03610918.2016.1263736>.

r-rmatio 0.19.0
Dependencies: zlib@1.3.1
Propagated dependencies: r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/stewid/rmatio
Licenses: GPL 3
Build system: r
Synopsis: Read and Write 'Matlab' Files
Description:

Read and write Matlab MAT files from R. The rmatio package supports reading MAT version 4, MAT version 5 and MAT compressed version 5. The rmatio package can write version 5 MAT files and version 5 files with variable compression.

r-reproduciblerchunks 1.2.0
Propagated dependencies: r-rstudioapi@0.17.1 r-rmarkdown@2.30 r-knitr@1.50 r-jsonlite@2.0.0 r-digest@0.6.39
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://cran.r-project.org/package=reproducibleRchunks
Licenses: Expat
Build system: r
Synopsis: Automated Reproducibility Checks for R Markdown Documents
Description:

Provide reproducible R chunks in R Markdown document that automatically check computational results for reproducibility. This is achieved by creating json files storing metadata about computational results. A comprehensive tutorial to the package is available as preprint by Brandmaier & Peikert (2024, <doi:10.31234/osf.io/3zjvf>).

r-rivnet 0.6.0
Propagated dependencies: r-traudem@1.0.3 r-terra@1.8-86 r-spam@2.11-1 r-sf@1.0-23 r-rcpp@1.1.0 r-raster@3.6-32 r-parallelly@1.45.1 r-ocnet@1.2.3 r-fields@17.1 r-elevatr@0.99.1 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://lucarraro.github.io/rivnet/
Licenses: Expat
Build system: r
Synopsis: Extract and Analyze Rivers from Elevation Data
Description:

Seamless extraction of river networks from digital elevation models data. The package allows analysis of digital elevation models that can be either externally provided or downloaded from open source repositories (thus interfacing with the elevatr package). Extraction is performed via the D8 flow direction algorithm of TauDEM (Terrain Analysis Using Digital Elevation Models), thus interfacing with the traudem package. Resulting river networks are compatible with functions from the OCNet package. See Carraro (2023) <doi:10.5194/hess-27-3733-2023> for a presentation of the package.

r-rlescalation 1.0.3
Propagated dependencies: r-zip@2.3.3 r-reticulate@1.44.1 r-r6@2.6.1 r-nleqslv@3.3.5 r-glue@1.8.0
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/MatsuuraKentaro/RLescalation
Licenses: Expat
Build system: r
Synopsis: Optimal Dose Escalation Using Deep Reinforcement Learning
Description:

An implementation to compute an optimal dose escalation rule using deep reinforcement learning in phase I oncology trials (Matsuura et al. (2023) <doi:10.1080/10543406.2023.2170402>). The dose escalation rule can directly optimize the percentages of correct selection (PCS) of the maximum tolerated dose (MTD).

r-rocbc 3.2.0
Propagated dependencies: r-splancs@2.01-45 r-proc@1.19.0.1 r-pracma@2.4.6 r-mvtnorm@1.3-3 r-mrmcaov@0.3.1 r-formattable@0.2.1 r-clinfun@1.1.5
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://cran.r-project.org/package=rocbc
Licenses: GPL 3
Build system: r
Synopsis: Statistical Inference for Box-Cox Based Receiver Operating Characteristic Curves
Description:

Generation of Box-Cox based ROC curves and several aspects of inferences and hypothesis testing. Can be used when inferences for one biomarker (Bantis LE, Nakas CT, Reiser B. (2018)<doi:10.1002/bimj.201700107>) are of interest or when comparisons of two correlated biomarkers (Bantis LE, Nakas CT, Reiser B. (2021)<doi:10.1002/bimj.202000128>) are of interest. Provides inferences and comparisons around the AUC, the Youden index, the sensitivity at a given specificity level (and vice versa), the optimal operating point of the ROC curve (in the Youden sense), and the Youden based cutoff.

r-rmcfs 1.3.6
Dependencies: openjdk@25
Propagated dependencies: r-yaml@2.3.10 r-stringi@1.8.7 r-rjava@1.0-11 r-reshape2@1.4.5 r-igraph@2.2.1 r-gridextra@2.3 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://home.ipipan.waw.pl/m.draminski/mcfs.html
Licenses: GPL 3
Build system: r
Synopsis: The MCFS-ID Algorithm for Feature Selection and Interdependency Discovery
Description:

MCFS-ID (Monte Carlo Feature Selection and Interdependency Discovery) is a Monte Carlo method-based tool for feature selection. It also allows for the discovery of interdependencies between the relevant features. MCFS-ID is particularly suitable for the analysis of high-dimensional, small n large p transactional and biological data. M. Draminski, J. Koronacki (2018) <doi:10.18637/jss.v085.i12>.

r-rcal 2.0
Propagated dependencies: r-trust@0.1-8
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: http://www.stat.rutgers.edu/~ztan
Licenses: GPL 2+
Build system: r
Synopsis: Regularized Calibrated Estimation
Description:

Regularized calibrated estimation for causal inference and missing-data problems with high-dimensional data, based on Tan (2020a) <doi:10.1093/biomet/asz059>, Tan (2020b) <doi:10.1214/19-AOS1824> and Sun and Tan (2020) <arXiv:2009.09286>.

r-rflexscan 1.2.0
Propagated dependencies: r-sf@1.0-23 r-rcpp@1.1.0 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://tkhrotn.github.io/rflexscan/
Licenses: GPL 3
Build system: r
Synopsis: The Flexible Spatial Scan Statistic
Description:

This package provides functions for detecting spatial clusters using the flexible spatial scan statistic developed by Tango and Takahashi (2005) <doi:10.1186/1476-072X-4-11>. This package implements a wrapper for the C routine used in the FleXScan 3.1.2 <https://sites.google.com/site/flexscansoftware/home> developed by Takahashi, Yokoyama, and Tango. For details, see Otani et al. (2021) <doi:10.18637/jss.v099.i13>.

r-robustanova 0.3.0
Propagated dependencies: r-peip@2.2-5 r-optimbase@1.0-10
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://cran.r-project.org/package=RobustANOVA
Licenses: GPL 3+
Build system: r
Synopsis: Robust One-Way ANOVA Tests under Heteroscedasticity and Nonnormality
Description:

Robust tests (RW, RPB and RGF) are provided for testing the equality of several long-tailed symmetric (LTS) means when the variances are unknown and arbitrary. RW, RPB and RGF tests are robust versions of Welch's F test proposed by Welch (1951) <doi:10.2307/2332579>, parametric bootstrap test proposed by Krishnamoorthy et. al (2007) <doi:10.1016/j.csda.2006.09.039>; and generalized F test proposed by Weerahandi (1995) <doi:10.2307/2532947>;, respectively. These tests are based on the modified maximum likelihood (MML) estimators proposed by Tiku(1967, 1968) <doi:10.2307/2333859>, <doi:10.1080/01621459.1968.11009228>.

r-rafs 0.2.5
Propagated dependencies: r-splittools@1.0.1 r-mdfs@1.5.5 r-fastcluster@1.3.0
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://www.mdfs.it/
Licenses: GPL 3
Build system: r
Synopsis: Robust Aggregative Feature Selection
Description:

This package provides a cross-validated minimal-optimal feature selection algorithm. It utilises popularity counting, hierarchical clustering with feature dissimilarity measures, and prefiltering with all-relevant feature selection method to obtain the minimal-optimal set of features.

r-rquefts 1.2-5
Propagated dependencies: r-rcpp@1.1.0 r-meteor@0.4-5
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://CRAN.R-project.org/package=Rquefts
Licenses: GPL 3+
Build system: r
Synopsis: Quantitative Evaluation of the Native Fertility of Tropical Soils
Description:

An implementation of the QUEFTS (Quantitative Evaluation of the Native Fertility of Tropical Soils) model. The model (1) estimates native nutrient (N, P, K) supply of soils from a few soil chemical properties; and (2) computes crop yield given that supply, crop parameters, fertilizer application, and crop attainable yield. See Janssen et al. (1990) <doi:10.1016/0016-7061(90)90021-Z> for the technical details and Sattari et al. (2014) <doi:10.1016/j.fcr.2013.12.005> for a recent evaluation and improvements.

r-rjdqa 0.1.6
Dependencies: openjdk@25
Propagated dependencies: r-rjdemetra@0.2.8 r-rjava@1.0-11 r-plotrix@3.8-13 r-ggdemetra@0.2.9
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://aqlt.github.io/rjdqa/
Licenses: FSDG-compatible
Build system: r
Synopsis: Quality Assessment for Seasonal Adjustment
Description:

Add-in to the RJDemetra package on seasonal adjustments. It allows to produce dashboards to summarise models and quickly check the quality of the seasonal adjustment.

r-rockr 1.0.0
Propagated dependencies: r-progress@1.2.3 r-mime@0.13 r-jsonlite@2.0.0 r-httr@1.4.7
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://cran.r-project.org/package=rockr
Licenses: Expat
Build system: r
Synopsis: 'Rock' R Server Client
Description:

Connector to the REST API of a Rock R server, to perform operations on a remote R server session, or administration tasks. See Rock documentation at <https://rockdoc.obiba.org/>.

r-rbnz 3.0.0
Propagated dependencies: r-xml2@1.5.0 r-rvest@1.0.5 r-readxl@1.4.5 r-lubridate@1.9.4 r-httr@1.4.7
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://cran.r-project.org/package=RBNZ
Licenses: Expat
Build system: r
Synopsis: Download Data from the Reserve Bank of New Zealand Website
Description:

This package provides a convenient way of accessing data published by the Reserve Bank of New Zealand (RBNZ) on their website, <https://www.rbnz.govt.nz/statistics>. A range of financial and economic data is provided in spreadsheet format including exchange and interest rates, commercial lending statistics, Reserve Bank market operations, financial institution statistics, household financial data, New Zealand debt security information, and economic indicators. This package provides a method to download those spreadsheets and read them directly into R.

r-rotations 1.6.6
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-gridextra@2.3 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/stanfill/rotationsC
Licenses: Expat
Build system: r
Synopsis: Working with Rotation Data
Description:

This package provides tools for working with rotational data, including simulation from the most commonly used distributions on SO(3), methods for different Bayes, mean and median type estimators for the central orientation of a sample, confidence/credible regions for the central orientation based on those estimators and a novel visualization technique for rotation data. Most recently, functions to identify potentially discordant (outlying) values have been added. References: Bingham, Melissa A. and Nordman, Dan J. and Vardeman, Steve B. (2009), Bingham, Melissa A and Vardeman, Stephen B and Nordman, Daniel J (2009), Bingham, Melissa A and Nordman, Daniel J and Vardeman, Stephen B (2010), Leon, C.A. and Masse, J.C. and Rivest, L.P. (2006), Hartley, R and Aftab, K and Trumpf, J. (2011), Stanfill, Bryan and Genschel, Ulrike and Hofmann, Heike (2013), Maonton, Jonathan (2004), Mardia, KV and Jupp, PE (2000, ISBN:9780471953333), Rancourt, D. and Rivest, L.P. and Asselin, J. (2000), Chang, Ted and Rivest, Louis-Paul (2001), Fisher, Nicholas I. (1996, ISBN:0521568900).

r-risk-assessr 3.0.1
Propagated dependencies: r-xml2@1.5.0 r-tidyr@1.3.1 r-stringr@1.6.0 r-rmarkdown@2.30 r-rlang@1.1.6 r-remotes@2.5.0 r-rcmdcheck@1.4.0 r-purrr@1.2.0 r-memoise@2.0.1 r-jsonlite@2.0.0 r-fs@1.6.6 r-dplyr@1.1.4 r-desc@1.4.3 r-curl@7.0.0 r-covr@3.6.5 r-checkmate@2.3.3 r-callr@3.7.6 r-biocmanager@1.30.27
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://sanofi-public.github.io/risk.assessr/
Licenses: GPL 2+
Build system: r
Synopsis: Assessing Package Risk Metrics
Description:

This package provides a reliable and validated tool that captures detailed risk metrics such as R CMD check, test coverage, traceability matrix, documentation, dependencies, reverse dependencies, suggested dependency analysis, repository data, and enhanced reporting for R packages that are local or stored on remote repositories such as GitHub, CRAN, and Bioconductor.

r-rema 0.0.1
Propagated dependencies: r-rdpack@2.6.4 r-rcpp@1.1.0 r-progress@1.2.3
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://cran.r-project.org/package=rema
Licenses: GPL 3+ FSDG-compatible
Build system: r
Synopsis: Rare Event Meta Analysis
Description:

The rema package implements a permutation-based approach for binary meta-analyses of 2x2 tables, founded on conditional logistic regression, that provides more reliable statistical tests when heterogeneity is observed in rare event data (Zabriskie et al. 2021 <doi:10.1002/sim.9142>). To adjust for the effect of heterogeneity, this method conditions on the sufficient statistic of a proxy for the heterogeneity effect as opposed to estimating the heterogeneity variance. While this results in the model not strictly falling under the random-effects framework, it is akin to a random-effects approach in that it assumes differences in variability due to treatment. Further, this method does not rely on large-sample approximations or continuity corrections for rare event data. This method uses the permutational distribution of the test statistic instead of asymptotic approximations for inference. The number of observed events drives the computation complexity for creating this permutational distribution. Accordingly, for this method to be computationally feasible, it should only be applied to meta-analyses with a relatively low number of observed events. To create this permutational distribution, a network algorithm, based on the work of Mehta et al. (1992) <doi:10.2307/1390598> and Corcoran et al. (2001) <doi:10.1111/j.0006-341x.2001.00941.x>, is employed using C++ and integrated into the package.

r-rcppsmc 0.2.9
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-fkf@0.2.6
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/rcppsmc/rcppsmc
Licenses: GPL 2+
Build system: r
Synopsis: Rcpp Bindings for Sequential Monte Carlo
Description:

R access to the Sequential Monte Carlo Template Classes by Johansen <doi:10.18637/jss.v030.i06> is provided. At present, four additional examples have been added, and the first example from the JSS paper has been extended. Further integration and extensions are planned.

r-reglogit 1.2-8
Propagated dependencies: r-mvtnorm@1.3-3 r-matrix@1.7-4 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://bobby.gramacy.com/r_packages/reglogit/
Licenses: LGPL 2.0+
Build system: r
Synopsis: Simulation-Based Regularized Logistic Regression
Description:

Regularized (polychotomous) logistic regression by Gibbs sampling. The package implements subtly different MCMC schemes with varying efficiency depending on the data type (binary v. binomial, say) and the desired estimator (regularized maximum likelihood, or Bayesian maximum a posteriori/posterior mean, etc.) through a unified interface. For details, see Gramacy & Polson (2012 <doi:10.1214/12-BA719>).

r-reslr 0.1.1
Propagated dependencies: r-tidyr@1.3.1 r-tidybayes@3.0.7 r-stringr@1.6.0 r-r2jags@0.8-9 r-purrr@1.2.0 r-posterior@1.6.1 r-plyr@1.8.9 r-ncdf4@1.24 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-geosphere@1.5-20 r-fields@17.1 r-fastdummies@1.7.5 r-dplyr@1.1.4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://github.com/maeveupton/reslr
Licenses: Expat
Build system: r
Synopsis: Modelling Relative Sea Level Data
Description:

The Bayesian modelling of relative sea-level data using a comprehensive approach that incorporates various statistical models within a unifying framework. Details regarding each statistical models; linear regression (Ashe et al 2019) <doi:10.1016/j.quascirev.2018.10.032>, change point models (Cahill et al 2015) <doi:10.1088/1748-9326/10/8/084002>, integrated Gaussian process models (Cahill et al 2015) <doi:10.1214/15-AOAS824>, temporal splines (Upton et al 2023) <arXiv:2301.09556>, spatio-temporal splines (Upton et al 2023) <arXiv:2301.09556> and generalised additive models (Upton et al 2023) <arXiv:2301.09556>. This package facilitates data loading, model fitting and result summarisation. Notably, it accommodates the inherent measurement errors found in relative sea-level data across multiple dimensions, allowing for their inclusion in the statistical models.

r-rebus-numbers 0.0-1.1
Propagated dependencies: r-rebus-base@0.0-3
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://cran.r-project.org/package=rebus.numbers
Licenses: FSDG-compatible
Build system: r
Synopsis: Numeric Extensions for the 'rebus' Package
Description:

Build regular expressions piece by piece using human readable code. This package contains number-related functionality, and is primarily intended to be used by package developers.

r-robsa 1.0.3
Propagated dependencies: r-survival@3.8-3 r-scales@1.4.0 r-runjags@2.2.2-5 r-rlang@1.1.6 r-rjags@4-17 r-rdpack@2.6.4 r-coda@0.19-4.1 r-bayestools@0.2.23
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://fbartos.github.io/RoBSA/
Licenses: GPL 3
Build system: r
Synopsis: Robust Bayesian Survival Analysis
Description:

This package provides a framework for estimating ensembles of parametric survival models with different parametric families. The RoBSA framework uses Bayesian model-averaging to combine the competing parametric survival models into a model ensemble, weights the posterior parameter distributions based on posterior model probabilities and uses Bayes factors to test for the presence or absence of the individual predictors or preference for a parametric family (Bartoš, Aust & Haaf, 2022, <doi:10.1186/s12874-022-01676-9>). The user can define a wide range of informative priors for all parameters of interest. The package provides convenient functions for summary, visualizations, fit diagnostics, and prior distribution calibration.

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