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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.

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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-netmeta 3.3-1
Propagated dependencies: r-mvtnorm@1.3-3 r-metafor@4.8-0 r-meta@8.2-1 r-matrix@1.7-4 r-mass@7.3-65 r-magrittr@2.0.4 r-magic@1.6-1 r-igraph@2.2.1 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-colorspace@2.1-2
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/guido-s/netmeta
Licenses: GPL 2+ FSDG-compatible
Build system: r
Synopsis: Network Meta-Analysis using Frequentist Methods
Description:

This package provides a comprehensive set of functions providing frequentist methods for network meta-analysis (Balduzzi et al., 2023) <doi:10.18637/jss.v106.i02> and supporting Schwarzer et al. (2015) <doi:10.1007/978-3-319-21416-0>, Chapter 8 "Network Meta-Analysis": - frequentist network meta-analysis following Rücker (2012) <doi:10.1002/jrsm.1058>; - additive network meta-analysis for combinations of treatments (Rücker et al., 2020) <doi:10.1002/bimj.201800167>; - network meta-analysis of binary data using the Mantel-Haenszel or non-central hypergeometric distribution method (Efthimiou et al., 2019) <doi:10.1002/sim.8158>, or penalised logistic regression (Evrenoglou et al., 2022) <doi:10.1002/sim.9562>; - rankograms and ranking of treatments by the Surface under the cumulative ranking curve (SUCRA) (Salanti et al., 2013) <doi:10.1016/j.jclinepi.2010.03.016>; - ranking of treatments using P-scores (frequentist analogue of SUCRAs without resampling) according to Rücker & Schwarzer (2015) <doi:10.1186/s12874-015-0060-8>; - split direct and indirect evidence to check consistency (Dias et al., 2010) <doi:10.1002/sim.3767>, (Efthimiou et al., 2019) <doi:10.1002/sim.8158>; - league table with network meta-analysis results; - comparison-adjusted funnel plot (Chaimani & Salanti, 2012) <doi:10.1002/jrsm.57>; - net heat plot and design-based decomposition of Cochran's Q according to Krahn et al. (2013) <doi:10.1186/1471-2288-13-35>; - measures characterizing the flow of evidence between two treatments by König et al. (2013) <doi:10.1002/sim.6001>; - automated drawing of network graphs described in Rücker & Schwarzer (2016) <doi:10.1002/jrsm.1143>; - partial order of treatment rankings ('poset') and Hasse diagram for poset (Carlsen & Bruggemann, 2014) <doi:10.1002/cem.2569>; (Rücker & Schwarzer, 2017) <doi:10.1002/jrsm.1270>; - contribution matrix as described in Papakonstantinou et al. (2018) <doi:10.12688/f1000research.14770.3> and Davies et al. (2022) <doi:10.1002/sim.9346>; - network meta-regression with a single continuous or binary covariate; - subgroup network meta-analysis.

r-nhsrwaitinglist 0.1.2
Propagated dependencies: r-rlang@1.1.6 r-randomnames@1.6-0.0 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://nhs-r-community.github.io/NHSRwaitinglist/
Licenses: Expat
Build system: r
Synopsis: Waiting List Metrics Using Queuing Theory
Description:

Waiting list management using queuing theory to analyse, predict and manage queues, based on the approach described in Fong et al. (2022) <doi:10.1101/2022.08.23.22279117>. Aimed at UK National Health Service (NHS) applications, waiting list summary statistics, target-value calculations, waiting list simulation, and scheduling functions are included.

r-nimble 1.4.0
Propagated dependencies: r-r6@2.6.1 r-pracma@2.4.6 r-numderiv@2016.8-1.1 r-igraph@2.2.1 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://r-nimble.org
Licenses: Modified BSD GPL 2+
Build system: r
Synopsis: MCMC, Particle Filtering, and Programmable Hierarchical Modeling
Description:

This package provides a system for writing hierarchical statistical models largely compatible with BUGS and JAGS', writing nimbleFunctions to operate models and do basic R-style math, and compiling both models and nimbleFunctions via custom-generated C++. NIMBLE includes default methods for MCMC, Laplace Approximation, deterministic nested approximations, Monte Carlo Expectation Maximization, and some other tools. The nimbleFunction system makes it easy to do things like implement new MCMC samplers from R, customize the assignment of samplers to different parts of a model from R, and compile the new samplers automatically via C++ alongside the samplers NIMBLE provides. NIMBLE extends the BUGS'/'JAGS language by making it extensible: New distributions and functions can be added, including as calls to external compiled code. Although most people think of MCMC as the main goal of the BUGS'/'JAGS language for writing models, one can use NIMBLE for writing arbitrary other kinds of model-generic algorithms as well. A full User Manual is available at <https://r-nimble.org>.

r-nichevol 0.1.20
Propagated dependencies: r-terra@1.8-86 r-stringr@1.6.0 r-geiger@2.0.11 r-castor@1.8.4 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/marlonecobos/nichevol
Licenses: GPL 3
Build system: r
Synopsis: Tools for Ecological Niche Evolution Assessment Considering Uncertainty
Description:

This package provides a collection of tools that allow users to perform critical steps in the process of assessing ecological niche evolution over phylogenies, with uncertainty incorporated explicitly in reconstructions. The method proposed here for ancestral reconstruction of ecological niches characterizes species niches using a bin-based approach that incorporates uncertainty in estimations. Compared to other existing methods, the approaches presented here reduce risk of overestimation of amounts and rates of ecological niche evolution. The main analyses include: initial exploration of environmental data in occurrence records and accessible areas, preparation of data for phylogenetic analyses, executing comparative phylogenetic analyses of ecological niches, and plotting for interpretations. Details on the theoretical background and methods used can be found in: Owens et al. (2020) <doi:10.1002/ece3.6359>, Peterson et al. (1999) <doi:10.1126/science.285.5431.1265>, Soberón and Peterson (2005) <doi:10.17161/bi.v2i0.4>, Peterson (2011) <doi:10.1111/j.1365-2699.2010.02456.x>, Barve et al. (2011) <doi:10.1111/ecog.02671>, Machado-Stredel et al. (2021) <doi:10.21425/F5FBG48814>, Owens et al. (2013) <doi:10.1016/j.ecolmodel.2013.04.011>, Saupe et al. (2018) <doi:10.1093/sysbio/syx084>, and Cobos et al. (2021) <doi:10.1111/jav.02868>.

r-nvctr 0.1.7
Propagated dependencies: r-pracma@2.4.6 r-magrittr@2.0.4
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://nvctr.ansperformance.eu
Licenses: Expat
Build system: r
Synopsis: The n-vector Approach to Geographical Position Calculations using an Ellipsoidal Model of Earth
Description:

The n-vector framework uses the normal vector to the Earth ellipsoid (called n-vector) as a non-singular position representation that turns out to be very convenient for practical position calculations. The n-vector is simple to use and gives exact answers for all global positions, and all distances, for both ellipsoidal and spherical Earth models. This package is a translation of the Matlab library from FFI, the Norwegian Defence Research Establishment, as described in Gade (2010) <doi:10.1017/S0373463309990415>.

r-netcom 2.1.7
Propagated dependencies: r-vegan@2.7-2 r-tibble@3.3.0 r-rlang@1.1.6 r-reshape2@1.4.5 r-pracma@2.4.6 r-pdist@1.2.1 r-optimx@2025-4.9 r-matrix@1.7-4 r-magrittr@2.0.4 r-igraph@2.2.1 r-ggraph@2.2.2 r-ggplot2@4.0.1 r-ggfortify@0.4.19 r-gensa@1.1.15 r-foreach@1.5.2 r-expm@1.0-0 r-dplyr@1.1.4 r-doparallel@1.0.17 r-clue@0.3-66
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/langendorfr/netcom
Licenses: GPL 3
Build system: r
Synopsis: NETwork COMparison Inference
Description:

Infer system functioning with empirical NETwork COMparisons. These methods are part of a growing paradigm in network science that uses relative comparisons of networks to infer mechanistic classifications and predict systemic interventions. They have been developed and applied in Langendorf and Burgess (2021) <doi:10.1038/s41598-021-99251-7>, Langendorf (2020) <doi:10.1201/9781351190831-6>, and Langendorf and Goldberg (2019) <doi:10.48550/arXiv.1912.12551>.

r-narray 0.5.2
Propagated dependencies: r-stringr@1.6.0 r-rcpp@1.1.0 r-progress@1.2.3
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/mschubert/narray
Licenses: ASL 2.0 FSDG-compatible
Build system: r
Synopsis: Subset- And Name-Aware Array Utility Functions
Description:

Stacking arrays according to dimension names, subset-aware splitting and mapping of functions, intersecting along arbitrary dimensions, converting to and from data.frames, and many other helper functions.

r-nord 1.0.0
Propagated dependencies: r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nord
Licenses: Expat
Build system: r
Synopsis: Arctic Ice Studio's Nord and Group of Seven Inspired Colour Palettes for 'ggplot2'
Description:

This package provides the Arctic Ice Studio's Nord and Group of Seven inspired colour palettes for use with ggplot2 via custom functions.

r-nntensor 1.3.0
Propagated dependencies: r-tagcloud@0.7.0 r-rtensor@1.4.9 r-plot3d@1.4.2 r-mass@7.3-65 r-ggplot2@4.0.1 r-fields@17.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/rikenbit/nnTensor
Licenses: Expat
Build system: r
Synopsis: Non-Negative Tensor Decomposition
Description:

Some functions for performing non-negative matrix factorization, non-negative CANDECOMP/PARAFAC (CP) decomposition, non-negative Tucker decomposition, and generating toy model data. See Andrzej Cichock et al (2009) and the reference section of GitHub README.md <https://github.com/rikenbit/nnTensor>, for details of the methods.

r-nicherover 1.1.2
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/mlysy/nicheROVER
Licenses: GPL 3
Build system: r
Synopsis: Niche Region and Niche Overlap Metrics for Multidimensional Ecological Niches
Description:

Implementation of a probabilistic method to calculate nicheROVER (_niche_ _r_egion and niche _over_lap) metrics using multidimensional niche indicator data (e.g., stable isotopes, environmental variables, etc.). The niche region is defined as the joint probability density function of the multidimensional niche indicators at a user-defined probability alpha (e.g., 95%). Uncertainty is accounted for in a Bayesian framework, and the method can be extended to three or more indicator dimensions. It provides directional estimates of niche overlap, accounts for species-specific distributions in multivariate niche space, and produces unique and consistent bivariate projections of the multivariate niche region. The article by Swanson et al. (2015) <doi:10.1890/14-0235.1> provides a detailed description of the methodology. See the package vignette for a worked example using fish stable isotope data.

r-netregr 1.0.1
Propagated dependencies: r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=netregR
Licenses: Expat
Build system: r
Synopsis: Regression of Network Responses
Description:

Regress network responses (both directed and undirected) onto covariates of interest that may be actor-, relation-, or network-valued. In addition, compute principled variance estimates of the coefficients assuming that the errors are jointly exchangeable. Missing data is accommodated. Additionally implements building and inversion of covariance matrices under joint exchangeability, and generates random covariance matrices from this class. For more detail on methods, see Marrs, Fosdick, and McCormick (2017) <arXiv:1701.05530>.

r-noia 0.97.3
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/lerouzic/noia
Licenses: GPL 2
Build system: r
Synopsis: Implementation of the Natural and Orthogonal InterAction (NOIA) Model
Description:

The NOIA model, as described extensively in Alvarez-Castro & Carlborg (2007), is a framework facilitating the estimation of genetic effects and genotype-to-phenotype maps. This package provides the basic tools to perform linear and multilinear regressions from real populations (provided the phenotype and the genotype of every individuals), estimating the genetic effects from different reference points, the genotypic values, and the decomposition of genetic variances in a multi-locus, 2 alleles system. This package is presented in Le Rouzic & Alvarez-Castro (2008).

r-nbconv 1.0.1
Propagated dependencies: r-matrixstats@1.5.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/gbedwell/nbconv
Licenses: GPL 3+
Build system: r
Synopsis: Evaluate Arbitrary Negative Binomial Convolutions
Description:

Three distinct methods are implemented for evaluating the sums of arbitrary negative binomial distributions. These methods are: Furman's exact probability mass function (Furman (2007) <doi:10.1016/j.spl.2006.06.007>), saddlepoint approximation, and a method of moments approximation. Functions are provided to calculate the density function, the distribution function and the quantile function of the convolutions in question given said evaluation methods. Functions for generating random deviates from negative binomial convolutions and for directly calculating the mean, variance, skewness, and excess kurtosis of said convolutions are also provided.

r-nonparquantilecausality 0.1.0
Propagated dependencies: r-quantreg@6.1 r-kernsmooth@2.23-26 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://www.mbalcilar.net
Licenses: Expat
Build system: r
Synopsis: Nonparametric Causality in Quantiles Test
Description:

This package implements the nonparametric causality-in-quantiles test (in mean or variance), returning a test object with an S3 plot() method. The current implementation uses one lag of each series (first-order Granger causality setup). Methodology is based on Balcilar, Gupta, and Pierdzioch (2016a) <doi:10.1016/j.resourpol.2016.04.004> and Balcilar et al. (2016) <doi:10.1007/s11079-016-9388-x>.

r-nlsem 0.8-1
Propagated dependencies: r-orthopolynom@1.0-6.1 r-nlme@3.1-168 r-mvtnorm@1.3-3 r-lavaan@0.6-20 r-gaussquad@1.0-3
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/nwickel/nlsem
Licenses: GPL 2+
Build system: r
Synopsis: Fitting Structural Equation Mixture Models
Description:

Estimation of structural equation models with nonlinear effects and underlying nonnormal distributions.

r-ncoder 0.2.0.1
Propagated dependencies: r-rhor@1.3.1 r-r6@2.6.1 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=ncodeR
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Techniques for Automated Classifiers
Description:

This package provides a set of techniques that can be used to develop, validate, and implement automated classifiers. A powerful tool for transforming raw data into meaningful information, ncodeR (Shaffer, D. W. (2017) Quantitative Ethnography. ISBN: 0578191687) is designed specifically for working with big data: large document collections, logfiles, and other text data.

r-novicedeveloperresources2 1.1.0
Propagated dependencies: r-novicedeveloperresources@1.2.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NoviceDeveloperResources2
Licenses: GPL 2+
Build system: r
Synopsis: Further Resources to Assist Novice Developers
Description:

Assist novice developers when preparing a single package or a set of integrated packages to submit to CRAN. Provide additional resources to facilitate the automation of the following individual or batch processing: check local source packages; build local .tar.gz source files; install packages from local .tar.gz files; detect conflicts between function names in the environment. The additional resources include determining the identity and ordering of the packages to process when updating an imported package.

r-npsurvss 1.1.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/godwinyyung/npsurvSS
Licenses: GPL 2
Build system: r
Synopsis: Sample Size and Power Calculation for Common Non-Parametric Tests in Survival Analysis
Description:

This package provides a number of statistical tests have been proposed to compare two survival curves, including the difference in (or ratio of) t-year survival, difference in (or ratio of) p-th percentile survival, difference in (or ratio of) restricted mean survival time, and the weighted log-rank test. Despite the multitude of options, the convention in survival studies is to assume proportional hazards and to use the unweighted log-rank test for design and analysis. This package provides sample size and power calculation for all of the above statistical tests with allowance for flexible accrual, censoring, and survival (eg. Weibull, piecewise-exponential, mixture cure). It is the companion R package to the paper by Yung and Liu (2020) <doi:10.1111/biom.13196>. Specific to the weighted log-rank test, users may specify which approximations they wish to use to estimate the large-sample mean and variance. The default option has been shown to provide substantial improvement over the conventional sample size and power equations based on Schoenfeld (1981) <doi:10.1093/biomet/68.1.316>.

r-nsga2r 1.1
Propagated dependencies: r-mco@1.17
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nsga2R
Licenses: LGPL 3
Build system: r
Synopsis: Elitist Non-Dominated Sorting Genetic Algorithm
Description:

Box-constrained multiobjective optimization using the elitist non-dominated sorting genetic algorithm - NSGA-II. Fast non-dominated sorting, crowding distance, tournament selection, simulated binary crossover, and polynomial mutation are called in the main program. The methods are described in Deb et al. (2002) <doi:10.1109/4235.996017>.

r-neotoma2 1.0.11
Propagated dependencies: r-uuid@1.2-1 r-tidyr@1.3.1 r-stringr@1.6.0 r-sf@1.0-23 r-rlang@1.1.6 r-purrr@1.2.0 r-progress@1.2.3 r-magrittr@2.0.4 r-leaflet@2.2.3 r-jsonlite@2.0.0 r-httr@1.4.7 r-geojsonsf@2.0.5 r-dplyr@1.1.4 r-digest@0.6.39 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/NeotomaDB/neotoma2
Licenses: Expat
Build system: r
Synopsis: Working with the Neotoma Paleoecology Database
Description:

Access and manipulation of data using the Neotoma Paleoecology Database. <https://api.neotomadb.org/api-docs/>. Examples in functions that require API access are not executed during CRAN checks. Vignettes do not execute as to avoid API calls during CRAN checks.

r-npi 0.2.0
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-purrr@1.2.0 r-magrittr@2.0.4 r-httr@1.4.7 r-glue@1.8.0 r-dplyr@1.1.4 r-curl@7.0.0 r-checkmate@2.3.3 r-checkluhn@1.1.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/ropensci/npi/
Licenses: Expat
Build system: r
Synopsis: Access the U.S. National Provider Identifier Registry API
Description:

Access the United States National Provider Identifier Registry API <https://npiregistry.cms.hhs.gov/api/>. Obtain and transform administrative data linked to a specific individual or organizational healthcare provider, or perform advanced searches based on provider name, location, type of service, credentials, and other attributes exposed by the API.

r-nett 1.0.0
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-matrix@1.7-4 r-magrittr@2.0.4 r-foreach@1.5.2
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/aaamini/nett
Licenses: Expat
Build system: r
Synopsis: Network Analysis and Community Detection
Description:

Features tools for the network data analysis and community detection. Provides multiple methods for fitting, model selection and goodness-of-fit testing in degree-corrected stochastic blocks models. Most of the computations are fast and scalable for sparse networks, esp. for Poisson versions of the models. Implements the following: Amini, Chen, Bickel and Levina (2013) <doi:10.1214/13-AOS1138> Bickel and Sarkar (2015) <doi:10.1111/rssb.12117> Lei (2016) <doi:10.1214/15-AOS1370> Wang and Bickel (2017) <doi:10.1214/16-AOS1457> Zhang and Amini (2020) <arXiv:2012.15047> Le and Levina (2022) <doi:10.1214/21-EJS1971>.

r-nltt 1.4.10
Propagated dependencies: r-testit@0.13 r-coda@0.19-4.1 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/thijsjanzen/nLTT
Licenses: GPL 2
Build system: r
Synopsis: Calculate the NLTT Statistic
Description:

This package provides functions to calculate the normalised Lineage-Through- Time (nLTT) statistic, given two phylogenetic trees. The nLTT statistic measures the difference between two Lineage-Through-Time curves, where each curve is normalised both in time and in number of lineages.

r-ndi 0.2.1
Propagated dependencies: r-units@1.0-0 r-tigris@2.2.1 r-tidyr@1.3.1 r-tidycensus@1.7.3 r-stringr@1.6.0 r-sf@1.0-23 r-psych@2.5.6 r-matrix@1.7-4 r-mass@7.3-65 r-hmisc@5.2-4 r-dplyr@1.1.4 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/idblr/ndi
Licenses: ASL 2.0
Build system: r
Synopsis: Neighborhood Deprivation Indices
Description:

Computes various geospatial indices of socioeconomic deprivation and disparity in the United States. Some indices are considered "spatial" because they consider the values of neighboring (i.e., adjacent) census geographies in their computation, while other indices are "aspatial" because they only consider the value within each census geography. Two types of aspatial neighborhood deprivation indices (NDI) are available: including: (1) based on Messer et al. (2006) <doi:10.1007/s11524-006-9094-x> and (2) based on Andrews et al. (2020) <doi:10.1080/17445647.2020.1750066> and Slotman et al. (2022) <doi:10.1016/j.dib.2022.108002> who use variables chosen by Roux and Mair (2010) <doi:10.1111/j.1749-6632.2009.05333.x>. Both are a decomposition of multiple demographic characteristics from the U.S. Census Bureau American Community Survey 5-year estimates (ACS-5; 2006-2010 onward). Using data from the ACS-5 (2005-2009 onward), the package can also compute indices of racial or ethnic residential segregation, including but limited to those discussed in Massey & Denton (1988) <doi:10.1093/sf/67.2.281>, and additional indices of socioeconomic disparity.

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