_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
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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-nregression 0.5.1
Propagated dependencies: r-simitation@0.0.7 r-data-table@1.17.8 r-covr@3.6.5
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nRegression
Licenses: GPL 3
Build system: r
Synopsis: Simulation-Based Calculations of Sample Size for Linear and Logistic Regression
Description:

This package provides a function designed to estimate the minimal sample size required to attain a specific statistical power in the context of linear regression and logistic regression models through simulations.

r-nasaweather 0.1.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/hadley/nasaweather
Licenses: Expat
Build system: r
Synopsis: Collection of Datasets from the ASA 2006 Data Expo
Description:

Tidied data from the ASA 2006 data expo, as well as a number of useful other related data sets.

r-networkscaleup 0.2-1
Propagated dependencies: r-trialr@0.1.6 r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-stanheaders@2.32.10 r-scales@1.4.0 r-rstan@2.32.7 r-rmtstat@0.3.1 r-rlang@1.1.6 r-readr@2.1.6 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-purrr@1.2.0 r-laplacesdemon@16.1.6 r-gridextra@2.3 r-glmmtmb@1.1.13 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-bh@1.87.0-1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/ilaga/networkscaleup
Licenses: GPL 3+
Build system: r
Synopsis: Network Scale-Up Models for Aggregated Relational Data
Description:

This package provides a variety of Network Scale-up Models for researchers to analyze Aggregated Relational Data, through the use of Stan and glmmTMB'. Also provides tools for model checking In this version, the package implements models from Laga, I., Bao, L., and Niu, X (2023) <doi:10.1080/01621459.2023.2165929>, Zheng, T., Salganik, M. J., and Gelman, A. (2006) <doi:10.1198/016214505000001168>, Killworth, P. D., Johnsen, E. C., McCarty, C., Shelley, G. A., and Bernard, H. R. (1998) <doi:10.1016/S0378-8733(96)00305-X>, and Killworth, P. D., McCarty, C., Bernard, H. R., Shelley, G. A., and Johnsen, E. C. (1998) <doi:10.1177/0193841X9802200205>.

r-ncf 1.3-3
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://ento.psu.edu/directory/onb1
Licenses: GPL 3
Build system: r
Synopsis: Spatial Covariance Functions
Description:

Spatial (cross-)covariance and related geostatistical tools: the nonparametric (cross-)covariance function , the spline correlogram, the nonparametric phase coherence function, local indicators of spatial association (LISA), (Mantel) correlogram, (Partial) Mantel test.

r-normalr 1.0.0
Propagated dependencies: r-shiny@1.11.1 r-rlang@1.1.6 r-purrr@1.2.0 r-mass@7.3-65 r-magrittr@2.0.4
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/kcha193/normalr
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Normalisation of Multiple Variables in Large-Scale Datasets
Description:

The robustness of many of the statistical techniques, such as factor analysis, applied in the social sciences rests upon the assumption of item-level normality. However, when dealing with real data, these assumptions are often not met. The Box-Cox transformation (Box & Cox, 1964) <http://www.jstor.org/stable/2984418> provides an optimal transformation for non-normal variables. Yet, for large datasets of continuous variables, its application in current software programs is cumbersome with analysts having to take several steps to normalise each variable. We present an R package normalr that enables researchers to make convenient optimal transformations of multiple variables in datasets. This R package enables users to quickly and accurately: (1) anchor all of their variables at 1.00, (2) select the desired precision with which the optimal lambda is estimated, (3) apply each unique exponent to its variable, (4) rescale resultant values to within their original X1 and X(n) ranges, and (5) provide original and transformed estimates of skewness, kurtosis, and other inferential assessments of normality.

r-networkcomparr 0.0.0.9
Propagated dependencies: r-reshape2@1.4.5 r-qgraph@1.9.8 r-networktools@1.6.0 r-igraph@2.2.1 r-gdata@3.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NetworkComparr
Licenses: GPL 2
Build system: r
Synopsis: Statistical Comparison of Networks
Description:

This package provides a permutation-based hypothesis test for statistical comparison of two networks based on the invariance measures of the R package NetworkComparisonTest by van Borkulo et al. (2022), <doi:10.1037/met0000476>: network structure invariance, global strength invariance, edge invariance, and various centrality measures. Edgelists from dependent or independent samples are used as input. These edgelists are generated from concept maps and summed into two comparable group networks. The networks can be directed or undirected.

r-nonprobest 0.2.4
Propagated dependencies: r-sampling@2.11 r-matrix@1.7-4 r-glmnet@4.1-10 r-e1071@1.7-16 r-caret@7.0-1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NonProbEst
Licenses: GPL 2+
Build system: r
Synopsis: Estimation in Nonprobability Sampling
Description:

Different inference procedures are proposed in the literature to correct for selection bias that might be introduced with non-random selection mechanisms. A class of methods to correct for selection bias is to apply a statistical model to predict the units not in the sample (super-population modeling). Other studies use calibration or Statistical Matching (statistically match nonprobability and probability samples). To date, the more relevant methods are weighting by Propensity Score Adjustment (PSA). The Propensity Score Adjustment method was originally developed to construct weights by estimating response probabilities and using them in Horvitzâ Thompson type estimators. This method is usually used by combining a non-probability sample with a reference sample to construct propensity models for the non-probability sample. Calibration can be used in a posterior way to adding information of auxiliary variables. Propensity scores in PSA are usually estimated using logistic regression models. Machine learning classification algorithms can be used as alternatives for logistic regression as a technique to estimate propensities. The package NonProbEst implements some of these methods and thus provides a wide options to work with data coming from a non-probabilistic sample.

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-nombre 0.4.1
Propagated dependencies: r-fracture@0.2.2
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://nombre.rossellhayes.com
Licenses: Expat
Build system: r
Synopsis: Number Names
Description:

Converts numeric vectors to character vectors of English number names. Provides conversion to cardinals, ordinals, numerators, and denominators. Supports negative and non-integer numbers.

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-nexus 0.6.0
Propagated dependencies: r-mass@7.3-65 r-khroma@1.17.0 r-isopleuros@1.4.0 r-dimensio@0.14.1 r-arkhe@1.11.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://codeberg.org/tesselle/nexus
Licenses: GPL 3+
Build system: r
Synopsis: Sourcing Archaeological Materials by Chemical Composition
Description:

Exploration and analysis of compositional data in the framework of Aitchison (1986, ISBN: 978-94-010-8324-9). This package provides tools for chemical fingerprinting and source tracking of ancient materials.

r-netutils 0.8.4
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/schochastics/netUtils/
Licenses: Expat
Build system: r
Synopsis: Collection of Tools for Network Analysis
Description:

This package provides a collection of network analytic (convenience) functions which are missing in other standard packages. This includes triad census with attributes <doi:10.1016/j.socnet.2019.04.003>, core-periphery models <doi:10.1016/S0378-8733(99)00019-2>, and several graph generators. Most functions are build upon igraph'.

r-navaeci 0.1.1
Propagated dependencies: r-expm@1.0-0 r-boundedgeworth@0.1.3
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NAVAECI
Licenses: GPL 3
Build system: r
Synopsis: Non-Asymptotically Valid and Asymptotically Exact (NAVAE) Confidence Intervals
Description:

This package implements the non-asymptotically valid and asymptotically exact confidence intervals in two cases: estimation of the mean, and estimation of (a linear combination of) the coefficients in a linear regression model, following (Derumigny, Girard and Guyonvarch, 2025) <doi:10.48550/arXiv.2507.16776>.

r-neuroim 0.0.6
Propagated dependencies: r-yaimpute@1.0-34.1 r-stringr@1.6.0 r-rgl@1.3.31 r-readr@2.1.6 r-rcpp@1.1.0 r-matrix@1.7-4 r-iterators@1.0.14 r-hash@2.2.6.3 r-assertthat@0.2.1 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=neuroim
Licenses: GPL 2+
Build system: r
Synopsis: Data Structures and Handling for Neuroimaging Data
Description:

This package provides a collection of data structures that represent volumetric brain imaging data. The focus is on basic data handling for 3D and 4D neuroimaging data. In addition, there are function to read and write NIFTI files and limited support for reading AFNI files.

r-netknitr 0.2.1
Propagated dependencies: r-visnetwork@2.1.4 r-shinydashboard@0.7.3 r-shiny@1.11.1 r-openxlsx@4.2.8.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=netknitr
Licenses: GPL 3
Build system: r
Synopsis: Knit Network Map for any Dataset
Description:

Designed to create interactive and visually compelling network maps using R Shiny. It allows users to quickly analyze CSV files and visualize complex relationships, structures, and connections within data by leveraging powerful network analysis libraries and dynamic web interfaces.

r-nproc 2.1.5
Propagated dependencies: r-tree@1.0-45 r-rocr@1.0-11 r-randomforest@4.7-1.2 r-naivebayes@1.0.0 r-mass@7.3-65 r-glmnet@4.1-10 r-e1071@1.7-16 r-ada@2.0-5
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: http://advances.sciencemag.org/content/4/2/eaao1659
Licenses: GPL 2
Build system: r
Synopsis: Neyman-Pearson (NP) Classification Algorithms and NP Receiver Operating Characteristic (NP-ROC) Curves
Description:

In many binary classification applications, such as disease diagnosis and spam detection, practitioners commonly face the need to limit type I error (i.e., the conditional probability of misclassifying a class 0 observation as class 1) so that it remains below a desired threshold. To address this need, the Neyman-Pearson (NP) classification paradigm is a natural choice; it minimizes type II error (i.e., the conditional probability of misclassifying a class 1 observation as class 0) while enforcing an upper bound, alpha, on the type I error. Although the NP paradigm has a century-long history in hypothesis testing, it has not been well recognized and implemented in classification schemes. Common practices that directly limit the empirical type I error to no more than alpha do not satisfy the type I error control objective because the resulting classifiers are still likely to have type I errors much larger than alpha. As a result, the NP paradigm has not been properly implemented for many classification scenarios in practice. In this work, we develop the first umbrella algorithm that implements the NP paradigm for all scoring-type classification methods, including popular methods such as logistic regression, support vector machines and random forests. Powered by this umbrella algorithm, we propose a novel graphical tool for NP classification methods: NP receiver operating characteristic (NP-ROC) bands, motivated by the popular receiver operating characteristic (ROC) curves. NP-ROC bands will help choose in a data adaptive way and compare different NP classifiers.

r-nic 0.0.2
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/thiyangt/nic
Licenses: CC0
Build system: r
Synopsis: Nature Inspired Colours
Description:

Color palettes based on nature inspired colours in "Sri Lanka".

r-nflverse 1.0.3
Propagated dependencies: r-rstudioapi@0.17.1 r-rlang@1.1.6 r-nflseedr@2.0.2 r-nflreadr@1.5.0 r-nflplotr@1.6.0 r-nflfastr@5.2.0 r-nfl4th@1.0.5 r-magrittr@2.0.4 r-crayon@1.5.3 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://nflverse.nflverse.com/
Licenses: Expat
Build system: r
Synopsis: Easily Install and Load the 'nflverse'
Description:

The nflverse is a set of packages dedicated to data of the National Football League. This package is designed to make it easy to install and load multiple nflverse packages in a single step. Learn more about the nflverse at <https://nflverse.nflverse.com/>.

r-nfunnn 1.0
Propagated dependencies: r-torch@0.16.3 r-fda@6.3.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nFunNN
Licenses: GPL 3+
Build system: r
Synopsis: Nonlinear Functional Principal Component Analysis using Neural Networks
Description:

Implementation for nFunNN method, which is a novel nonlinear functional principal component analysis method using neural networks. The crucial function of this package is nFunNNmodel().

r-nodesub 1.2.9
Propagated dependencies: r-tracerer@2.2.3 r-tibble@3.3.0 r-testit@0.13 r-stringr@1.6.0 r-rmpfr@1.1-2 r-rcpp@1.1.0 r-rappdirs@0.3.3 r-phylobase@0.8.12 r-phangorn@2.12.1 r-pbapply@1.7-4 r-lifecycle@1.0.4 r-geiger@2.0.11 r-ddd@5.2.4 r-beautier@2.6.12 r-beastier@2.5.2 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/thijsjanzen/nodeSub
Licenses: GPL 3
Build system: r
Synopsis: Simulate DNA Alignments Using Node Substitutions
Description:

Simulate DNA sequences for the node substitution model. In the node substitution model, substitutions accumulate additionally during a speciation event, providing a potential mechanistic explanation for substitution rate variation. This package provides tools to simulate such a process, simulate a reference process with only substitutions along the branches, and provides tools to infer phylogenies from alignments. More information can be found in Janzen (2021) <doi:10.1093/sysbio/syab085>.

r-nbalover 0.1.3.3
Propagated dependencies: r-tidyr@1.3.1 r-magrittr@2.0.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NBAloveR
Licenses: GPL 2
Build system: r
Synopsis: Help Basketball Data Analysis
Description:

This package provides interface to the online basketball data resources such as Basketball reference API <https://www.basketball-reference.com/> and helps R users analyze basketball data.

r-netstat 0.1.2
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/stevecondylios/netstat
Licenses: Expat
Build system: r
Synopsis: Retrieve Network Statistics Including Available TCP Ports
Description:

R interface for the netstat command line utility used to retrieve and parse commonly used network statistics, including available and in-use transmission control protocol (TCP) ports. Primers offering technical background information on the netstat command line utility are available in the "Linux System Administrator's Manual" by Michael Kerrisk (2014) <https://man7.org/linux/man-pages/man8/netstat.8.html>, and on the Microsoft website (2017) <https://docs.microsoft.com/en-us/windows-server/administration/windows-commands/netstat>.

r-npbayesimputecat 0.6
Propagated dependencies: r-rlang@1.1.6 r-reshape2@1.4.5 r-rcpp@1.1.0 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-coda@0.19-4.1 r-bayesplot@1.14.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NPBayesImputeCat
Licenses: GPL 3+
Build system: r
Synopsis: Non-Parametric Bayesian Multiple Imputation for Categorical Data
Description:

These routines create multiple imputations of missing at random categorical data, and create multiply imputed synthesis of categorical data, with or without structural zeros. Imputations and syntheses are based on Dirichlet process mixtures of multinomial distributions, which is a non-parametric Bayesian modeling approach that allows for flexible joint modeling, described in Manrique-Vallier and Reiter (2014) <doi:10.1080/10618600.2013.844700>.

r-nettskjemar 1.0.4
Propagated dependencies: r-jsonlite@2.0.0 r-httr2@1.2.1 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/CAPRO-UiO/nettskjemar
Licenses: Expat
Build system: r
Synopsis: Connect to the 'nettskjema.no' API of the University of Oslo
Description:

Enables users to retrieve data, meta-data, and codebooks from <https://nettskjema.no/>. The data from the API is richer than from the online data portal. This package is not developed by the University of Oslo IT. Mowinckel (2021) <doi:10.5281/zenodo.4745481>.

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