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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-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-nacho 2.0.6
Dependencies: pandoc@2.19.2 pandoc@2.19.2
Propagated dependencies: r-shinywidgets@0.9.0 r-shiny@1.11.1 r-rmarkdown@2.30 r-knitr@1.50 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-ggforce@0.5.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/mcanouil/NACHO/
Licenses: GPL 3
Build system: r
Synopsis: NanoString Quality Control Dashboard
Description:

NanoString nCounter data are gene expression assays where there is no need for the use of enzymes or amplification protocols and work with fluorescent barcodes (Geiss et al. (2018) <doi:10.1038/nbt1385>). Each barcode is assigned a messenger-RNA/micro-RNA (mRNA/miRNA) which after bonding with its target can be counted. As a result each count of a specific barcode represents the presence of its target mRNA/miRNA. NACHO (NAnoString quality Control dasHbOard) is able to analyse the exported NanoString nCounter data and facilitates the user in performing a quality control. NACHO does this by visualising quality control metrics, expression of control genes, principal components and sample specific size factors in an interactive web application.

r-neutralitytestr 0.0.3
Propagated dependencies: r-scales@1.4.0 r-pracma@2.4.6 r-ggpmisc@0.6.2 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-cowplot@1.2.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/marcjwilliams1/neutralitytestr
Licenses: Expat
Build system: r
Synopsis: Test for a Neutral Evolutionary Model in Cancer Sequencing Data
Description:

Package takes frequencies of mutations as reported by high throughput sequencing data from cancer and fits a theoretical neutral model of tumour evolution. Package outputs summary statistics and contains code for plotting the data and model fits. See Williams et al 2016 <doi:10.1038/ng.3489> and Williams et al 2017 <doi:10.1101/096305> for further details of the method.

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-ntss 0.1.3
Propagated dependencies: r-spatstat-univar@3.1-5 r-spatstat-random@3.4-3 r-spatstat-model@3.5-0 r-spatstat-geom@3.6-1 r-spatstat-explore@3.6-0 r-spatstat@3.4-1 r-ks@1.15.1 r-get@1.0-7 r-geor@1.9-6
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NTSS
Licenses: GPL 3
Build system: r
Synopsis: Nonparametric Tests in Spatial Statistics
Description:

Nonparametric test of independence between a pair of spatial objects (random fields, point processes) based on random shifts with torus or variance correction. See MrkviÄ ka et al. (2021) <doi:10.1016/j.spasta.2020.100430>, DvoŠák et al. (2022) <doi:10.1111/insr.12503>, DvoŠák and MrkviÄ ka (2024) <doi:10.1080/10618600.2024.2357626>.

r-nasadata 0.9.0
Propagated dependencies: r-png@0.1-8 r-plyr@1.8.9 r-jsonlite@2.0.0 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=nasadata
Licenses: CC0
Build system: r
Synopsis: Interface to Various NASA API's
Description:

This package provides functions to access NASA's Earth Imagery and Assets API and the Earth Observatory Natural Event Tracker (EONET) webservice.

r-noncomplyr 1.0
Propagated dependencies: r-mcmcpack@1.7-1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=noncomplyR
Licenses: GPL 2
Build system: r
Synopsis: Bayesian Analysis of Randomized Experiments with Non-Compliance
Description:

This package provides functions for Bayesian analysis of data from randomized experiments with non-compliance. The functions are based on the models described in Imbens and Rubin (1997) <doi:10.1214/aos/1034276631>. Currently only two types of outcome models are supported: binary outcomes and normally distributed outcomes. Models can be fit with and without the exclusion restriction and/or the strong access monotonicity assumption. Models are fit using the data augmentation algorithm as described in Tanner and Wong (1987) <doi:10.2307/2289457>.

r-nipponmap 0.2
Propagated dependencies: r-tibble@3.3.0 r-sf@1.0-23
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NipponMap
Licenses: GPL 2+
Build system: r
Synopsis: Japanese Map Data and Functions
Description:

Digital map data of Japan for choropleth mapping, including a circle cartogram.

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-needs 0.0.3
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/joshkatz/needs
Licenses: Expat
Build system: r
Synopsis: Attaches and Installs Packages
Description:

This package provides a simple function for easier package loading and auto-installation.

r-nucim 1.0.13
Propagated dependencies: r-stringr@1.6.0 r-fields@17.1 r-ebimage@4.52.0 r-bioimagetools@1.1.9
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://bioimaginggroup.github.io/nucim/
Licenses: GPL 3
Build system: r
Synopsis: Nucleome Imaging Toolbox
Description:

This package provides tools for 4D nucleome imaging. Quantitative analysis of the 3D nuclear landscape recorded with super-resolved fluorescence microscopy. See Volker J. Schmid, Marion Cremer, Thomas Cremer (2017) <doi:10.1016/j.ymeth.2017.03.013>.

r-nlpwavelet 1.1
Propagated dependencies: r-wavethresh@4.7.3 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://nilotpalsanyal.github.io/NLPwavelet/
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Wavelet Analysis Using Non-Local Priors
Description:

This package performs Bayesian wavelet analysis using individual non-local priors as described in Sanyal & Ferreira (2017) <DOI:10.1007/s13571-016-0129-3> and non-local prior mixtures as described in Sanyal (2025) <DOI:10.48550/arXiv.2501.18134>.

r-nhsnumber 0.1.2
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/sellorm/nhsnumber
Licenses: Expat
Build system: r
Synopsis: Tools for Working with NHS Number Checksums
Description:

This package provides functions for working with NHS number checksums. The UK's National Health Service issues NHS numbers to all users of its services and this package implements functions for verifying that the numbers are valid according to the checksum scheme the NHS use. Numbers can be validated and checksums created.

r-nightday 1.0.1.1
Propagated dependencies: r-maps@3.4.3
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NightDay
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Night and Day Boundary Plot Function
Description:

Computes and plots the boundary between night and day.

r-namedropr 2.4.1
Propagated dependencies: r-webshot@0.5.5 r-stringr@1.6.0 r-readr@2.1.6 r-r-utils@2.13.0 r-qrcode@0.3.0 r-lubridate@1.9.4 r-htmltools@0.5.8.1 r-dplyr@1.1.4 r-bib2df@1.1.2.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/nucleic-acid/namedropR
Licenses: Expat
Build system: r
Synopsis: Create Visual Citations for Presentations and Posters
Description:

This package provides visual citations containing the metadata of a scientific paper and a QR code. A visual citation is a banner containing title, authors, journal and year of a publication. This package can create such banners based on BibTeX and BibLaTeX references or call the reference metadata from Crossref'-API. The banners include a QR code pointing to the DOI'. The resulting HTML object or PNG image can be included in a presentation to point the audience to good resources for further reading. Styling is possible via predefined designs or via custom CSS'. This package is not intended as replacement for proper reference manager packages, but a tool to enrich scientific presentation slides and conference posters.

r-nca 4.0.5
Propagated dependencies: r-truncnorm@1.0-9 r-quantreg@6.1 r-plotly@4.11.0 r-lpsolve@5.6.23 r-kernsmooth@2.23-26 r-iterators@1.0.14 r-gplots@3.2.0 r-ggplot2@4.0.1 r-foreach@1.5.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://www.eur.nl/en/erim/erim/research-initiatives/necessary-condition-analysis
Licenses: GPL 3+
Build system: r
Synopsis: Necessary Condition Analysis
Description:

This package performs a Necessary Condition Analysis (NCA). (Dul, J. 2016. Necessary Condition Analysis (NCA). Logic and Methodology of Necessary but not Sufficient causality." Organizational Research Methods 19(1), 10-52) <doi:10.1177/1094428115584005>. NCA identifies necessary (but not sufficient) conditions in datasets, where x causes (e.g. precedes) y. Instead of drawing a regression line through the middle of the data in an xy-plot, NCA draws the ceiling line. The ceiling line y = f(x) separates the area with observations from the area without observations. (Nearly) all observations are below the ceiling line: y <= f(x). The empty zone is in the upper left hand corner of the xy-plot (with the convention that the x-axis is horizontal and the y-axis is vertical and that values increase upwards and to the right''). The ceiling line is a (piecewise) linear non-decreasing line: a linear step function or a straight line. It indicates which level of x (e.g. an effort or input) is necessary but not sufficient for a (desired) level of y (e.g. good performance or output). A quick start guide for using this package can be found here: <https://repub.eur.nl/pub/78323/> or <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2624981>.

r-numosl 2.8
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://CRAN.R-project.org/package=numOSL
Licenses: GPL 3
Build system: r
Synopsis: Numeric Routines for Optically Stimulated Luminescence Dating
Description:

Optimizing regular numeric problems in optically stimulated luminescence dating, such as: equivalent dose calculation, dose rate determination, growth curve fitting, decay curve decomposition, statistical age model optimization, and statistical plot visualization.

r-nonmem2r 0.2.5
Propagated dependencies: r-splines2@0.5.4 r-reshape2@1.4.5 r-mvtnorm@1.3-3 r-mass@7.3-65 r-latticeextra@0.6-31 r-lattice@0.22-7 r-gridextra@2.3 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=nonmem2R
Licenses: FSDG-compatible
Build system: r
Synopsis: Loading NONMEM Output Files with Functions for Visual Predictive Checks (VPC) and Goodness of Fit (GOF) Plots
Description:

Loading NONMEM (NONlinear Mixed-Effect Modeling, <https://www.iconplc.com/solutions/technologies/nonmem/>) and PSN (Perl-speaks-NONMEM, <https://uupharmacometrics.github.io/PsN/>) output files to extract parameter estimates, provide visual predictive check (VPC) and goodness of fit (GOF) plots, and simulate with parameter uncertainty.

r-nppbib 1.2-0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/dalling1
Licenses: GPL 3
Build system: r
Synopsis: Nonparametric Partially-Balanced Incomplete Block Design Analysis
Description:

This package implements a nonparametric statistical test for rank or score data from partially-balanced incomplete block-design experiments.

r-nrlr 0.1.2
Propagated dependencies: r-xml2@1.5.0 r-tibble@3.3.0 r-stringr@1.6.0 r-rvest@1.0.5 r-purrr@1.2.0 r-lubridate@1.9.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-glue@1.8.0 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://github.com/DanielTomaro13/nrlR
Licenses: Expat
Build system: r
Synopsis: Functions to Scrape Rugby Data
Description:

This package provides a set of functions to scrape and analyze rugby data. Supports competitions including the National Rugby League, New South Wales Cup, Queensland Cup, Super League, and various representative and women's competitions. Includes functions to fetch player statistics, match results, ladders, venues, and coaching data. Designed to assist analysts, fans, and researchers in exploring historical and current rugby league data. See Woods et al. (2017) <doi:10.1123/ijspp.2016-0187> for an example of rugby league performance analysis methodology.

r-nutrition 1.1.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://wleoncio.github.io/nutrition/
Licenses: GPL 3+
Build system: r
Synopsis: Useful Functions for People on a Diet
Description:

This package contains a collection of functions for performing different kinds of calculation that are of interest to someone following a diet plan. Calculators for the Basal Metabolic Rate are based on Mifflin et al. (1990) <doi:10.1093/ajcn/51.2.241> and McArdle, W. D., Katch, F. I., & Katch, V. L. (2010, ISBN:9780812109917).

r-neurodatasets 0.3.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/lightbluetitan/neurodatasets
Licenses: GPL 3
Build system: r
Synopsis: Comprehensive Collection of Neuroscience and Brain-Related Datasets
Description:

Offers a rich and diverse collection of datasets focused on the brain, nervous system, and related disorders. The package includes clinical, experimental, neuroimaging, behavioral, cognitive, and simulated data on conditions such as Parkinson's disease, Alzheimer's disease, dementia, epilepsy, schizophrenia, autism spectrum disorder, attention deficit, hyperactivity disorder, Tourette's syndrome, traumatic brain injury, gliomas, migraines, headaches, sleep disorders, concussions, encephalitis, subarachnoid hemorrhage, and mental health conditions. Datasets cover structural and functional brain data, cross-sectional and longitudinal MRI imaging studies, neurotransmission, gene expression, cognitive performance, intelligence metrics, sleep deprivation effects, treatment outcomes, brain-body relationships across species, neurological injury patterns, and acupuncture interventions. Data sources include peer-reviewed studies, clinical trials, military health records, sports injury databases, and international comparative studies. Designed for researchers, neuroscientists, clinicians, psychologists, data scientists, and students, this package facilitates exploratory data analysis, statistical modeling, and hypothesis testing in neuroscience and neuroepidemiology.

r-ntranova 0.0.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=ntranova
Licenses: GPL 3
Build system: r
Synopsis: Two Way Neutrosophic ANOVA
Description:

Dealing with neutrosophic data of the form N=D+I(where N is a Neutrosophic number ,D is the determinant part of the number and I is the indeterminacy part) using the neutrosophic two way anova test keeps the type I error low. This algorithm calculates the fisher statistics when we have a neutrosophic data, also tests two hypothesizes, first is to test differences between treatments, and second is to test differences between sectors. For more information see Miari, Mahmoud; Anan, Mohamad Taher; Zeina, Mohamed Bisher(2022) <https://www.americaspg.com/articleinfo/21/show/1058>.

r-npbbbdaefficiency 0.1.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NPBBBDAefficiency
Licenses: GPL 3
Build system: r
Synopsis: A-Efficiency for Nested Partially Balanced Bipartite Block (NPBBB) Designs
Description:

Nested Partially Balanced Bipartite Block (NPBBB) designs involve two levels of blocking: (i) The block design (ignoring sub-block classification) serves as a partially balanced bipartite block (PBBB) design, and (ii) The sub-block design (ignoring block classification) also serves as a PBBB design. More details on constructions of the PBBB designs and their characterization properties are available in Vinayaka et al.(2023) <doi:10.1080/03610926.2023.2251623>. This package calculates A-efficiency values for both block and sub-block structures, along with all parameters of a given NPBBB design.

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