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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-natcpp 0.2
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/natverse/natcpp
Licenses: GPL 3+
Build system: r
Synopsis: Fast C++ Primitives for the 'NeuroAnatomy Toolbox'
Description:

Fast functions implemented in C++ via Rcpp to support the NeuroAnatomy Toolbox ('nat') ecosystem. These functions provide large speed-ups for basic manipulation of neuronal skeletons over pure R functions found in the nat package. The expectation is that end users will not use this package directly, but instead the nat package will automatically use routines from this package when it is available to enable large performance gains.

r-normpsy 1.0.8
Propagated dependencies: r-lcmm@2.2.2
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NormPsy
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Normalisation of Psychometric Tests
Description:

This package provides functions for normalizing psychometric test scores. The normalization aims at correcting the metrological properties of the psychometric tests such as the ceiling and floor effects and the curvilinearity (unequal interval scaling). Functions to compute and plot predictions in the natural scale of the psychometric test from the estimates of a linear mixed model estimated on the normalized scores are also provided. See Philipps et al (2014) <doi:10.1159/000365637> for details.

r-nonlineartsa 0.5.0
Propagated dependencies: r-tsdyn@11.0.5.2 r-minpack-lm@1.2-4 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NonlinearTSA
Licenses: GPL 2+
Build system: r
Synopsis: Nonlinear Time Series Analysis
Description:

Function and data sets in the book entitled "Nonlinear Time Series Analysis with R Applications" B.Guris (2020). The book will be published in Turkish and the original name of this book will be "R Uygulamali Dogrusal Olmayan Zaman Serileri Analizi". It is possible to perform nonlinearity tests, nonlinear unit root tests, nonlinear cointegration tests and estimate nonlinear error correction models by using the functions written in this package. The Momentum Threshold Autoregressive (MTAR), the Smooth Threshold Autoregressive (STAR) and the Self Exciting Threshold Autoregressive (SETAR) type unit root tests can be performed using the functions written. In addition, cointegration tests using the Momentum Threshold Autoregressive (MTAR), the Smooth Threshold Autoregressive (STAR) and the Self Exciting Threshold Autoregressive (SETAR) models can be applied. It is possible to estimate nonlinear error correction models. The Granger causality test performed using nonlinear models can also be applied.

r-nna 0.0.2.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nna
Licenses: GPL 2+
Build system: r
Synopsis: Nearest-Neighbor Analysis
Description:

Calculates spatial pattern analysis using a T-square sample procedure. This method is based on two measures "x" and "y". "x" - Distance from the random point to the nearest individual. "y" - Distance from individual to its nearest neighbor. This is a methodology commonly used in phytosociology or marine benthos ecology to analyze the species distribution (random, uniform or clumped patterns). Ludwig & Reynolds (1988, ISBN:0471832359).

r-negbinbetabinreg 1.0
Propagated dependencies: r-mvtnorm@1.3-3 r-matrix@1.7-4 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NegBinBetaBinreg
Licenses: GPL 2+
Build system: r
Synopsis: Negative Binomial and Beta Binomial Bayesian Regression Models
Description:

The Negative Binomial regression with mean and shape modeling and mean and variance modeling and Beta Binomial regression with mean and dispersion modeling.

r-normmix 0.2-0
Propagated dependencies: r-sfsmisc@1.1-23 r-mvtnorm@1.3-3 r-mclust@6.1.2 r-mass@7.3-65 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=norMmix
Licenses: GPL 3+
Build system: r
Synopsis: Direct MLE for Multivariate Normal Mixture Distributions
Description:

Multivariate Normal (i.e. Gaussian) Mixture Models (S3) Classes. Fitting models to data using MLE (maximum likelihood estimation) for multivariate normal mixtures via smart parametrization using the LDL (Cholesky) decomposition, see McLachlan and Peel (2000, ISBN:9780471006268), Celeux and Govaert (1995) <doi:10.1016/0031-3203(94)00125-6>.

r-necountries 0.1-1
Propagated dependencies: r-tibble@3.3.0 r-stringr@1.6.0 r-stringi@1.8.7 r-sf@1.0-23 r-rlang@1.1.6 r-rdpack@2.6.4 r-magrittr@2.0.4 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-classint@0.4-11
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://www.R-project.org
Licenses: GPL 2+
Build system: r
Synopsis: Countries of the World
Description:

Based on Natural Earth <https://www.naturalearthdata.com/>, a subset of countries can easily be selected with their administrative boundaries, joined with an external data frame and plotted as a thematic map.

r-neuralestimators 0.2.0
Dependencies: julia@1.8.5
Propagated dependencies: r-magrittr@2.0.4 r-juliaconnector@1.1.5
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/msainsburydale/NeuralEstimators
Licenses: GPL 2+
Build system: r
Synopsis: Likelihood-Free Parameter Estimation using Neural Networks
Description:

An R interface to the Julia package NeuralEstimators.jl'. The package facilitates the user-friendly development of neural Bayes estimators, which are neural networks that map data to a point summary of the posterior distribution (Sainsbury-Dale et al., 2024, <doi:10.1080/00031305.2023.2249522>). These estimators are likelihood-free and amortised, in the sense that, once the neural networks are trained on simulated data, inference from observed data can be made in a fraction of the time required by conventional approaches. The package also supports amortised Bayesian or frequentist inference using neural networks that approximate the posterior or likelihood-to-evidence ratio (Zammit-Mangion et al., 2025, Sec. 3.2, 5.2, <doi:10.48550/arXiv.2404.12484>). The package accommodates any model for which simulation is feasible by allowing users to define models implicitly through simulated data.

r-nlmixr2rpt 0.2.2
Propagated dependencies: r-yaml@2.3.10 r-xpose-nlmixr2@0.4.1 r-xpose@0.4.22 r-stringr@1.6.0 r-rxode2@5.0.1 r-onbrand@1.0.8 r-nlmixr2extra@5.0.0 r-nlmixr2est@5.0.2 r-ggpubr@0.6.2 r-ggplot2@4.0.1 r-ggforce@0.5.0 r-flextable@0.9.10 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://nlmixr2.github.io/nlmixr2rpt/
Licenses: GPL 3+
Build system: r
Synopsis: Templated Word and PowerPoint Reporting of 'nlmixr2' Fitting Results
Description:

This allows you to generate reporting workflows around nlmixr2 analyses with outputs in Word and PowerPoint. You can specify figures, tables and report structure in a user-definable YAML file. Also you can use the internal functions to access the figures and tables to allow their including in other outputs (e.g. R Markdown).

r-nmar 0.1.2
Propagated dependencies: r-nleqslv@3.3.5 r-generics@0.1.4 r-formula@1.2-5
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/ncn-foreigners/NMAR
Licenses: Expat
Build system: r
Synopsis: Estimation under not Missing at Random Nonresponse
Description:

This package provides methods to estimate finite-population parameters under nonresponse that is not missing at random (NMAR, nonignorable). Incorporates auxiliary information and user-specified response models, and supports independent samples and complex survey designs via objects from the survey package. Provides diagnostics and optional variance estimates. For methodological background see Qin, Leung and Shao (2002) <doi:10.1198/016214502753479338> and Riddles, Kim and Im (2016) <doi:10.1093/jssam/smv047>.

r-nonsmooth 1.0.0
Propagated dependencies: r-reshape2@1.4.5 r-np@0.60-18
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/jrjthompson/R-package-nonsmooth/
Licenses: FSDG-compatible
Build system: r
Synopsis: Nonparametric Methods for Smoothing Nonsmooth Data
Description:

Nonparametric methods for smoothing regression function data with change-points, utilizing range kernels for iterative and anisotropic smoothing methods. For further details, see the paper by John R.J. Thompson (2024) <doi:10.1080/02664763.2024.2352759>.

r-npsf 0.8.0
Propagated dependencies: r-rcpp@1.1.0 r-formula@1.2-5
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=npsf
Licenses: GPL 2
Build system: r
Synopsis: Nonparametric and Stochastic Efficiency and Productivity Analysis
Description:

Nonparametric efficiency measurement and statistical inference via DEA type estimators (see Färe, Grosskopf, and Lovell (1994) <doi:10.1017/CBO9780511551710>, Kneip, Simar, and Wilson (2008) <doi:10.1017/S0266466608080651> and Badunenko and Mozharovskyi (2020) <doi:10.1080/01605682.2019.1599778>) as well as Stochastic Frontier estimators for both cross-sectional data and 1st, 2nd, and 4th generation models for panel data (see Kumbhakar and Lovell (2003) <doi:10.1017/CBO9781139174411>, Badunenko and Kumbhakar (2016) <doi:10.1016/j.ejor.2016.04.049>). The stochastic frontier estimators can handle both half-normal and truncated normal models with conditional mean and heteroskedasticity. The marginal effects of determinants can be obtained.

r-nfactors 2.4.1.2
Propagated dependencies: r-psych@2.5.6 r-mass@7.3-65 r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nFactors
Licenses: GPL 3
Build system: r
Synopsis: Parallel Analysis and Other Non Graphical Solutions to the Cattell Scree Test
Description:

Indices, heuristics, simulations and strategies to help determine the number of factors/components to retain in exploratory factor analysis and principal component analysis.

r-nat 1.8.25
Propagated dependencies: r-yaml@2.3.10 r-rgl@1.3.31 r-plyr@1.8.9 r-nat-utils@0.6.1 r-nabor@0.5.0 r-igraph@2.2.1 r-filehash@2.4-6 r-digest@0.6.39
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/natverse/nat
Licenses: GPL 3
Build system: r
Synopsis: NeuroAnatomy Toolbox for Analysis of 3D Image Data
Description:

NeuroAnatomy Toolbox (nat) enables analysis and visualisation of 3D biological image data, especially traced neurons. Reads and writes 3D images in NRRD and Amira AmiraMesh formats and reads surfaces in Amira hxsurf format. Traced neurons can be imported from and written to SWC and Amira LineSet and SkeletonGraph formats. These data can then be visualised in 3D via rgl', manipulated including applying calculated registrations, e.g. using the CMTK registration suite, and analysed. There is also a simple representation for neurons that have been subjected to 3D skeletonisation but not formally traced; this allows morphological comparison between neurons including searches and clustering (via the nat.nblast extension package).

r-nlms 1.1
Propagated dependencies: r-nlme@3.1-168
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nlMS
Licenses: GPL 3
Build system: r
Synopsis: Non-Linear Model Selection
Description:

Package to select best model among several linear and nonlinear models. The main function uses the gnls() function from the nlme package to fit the data to nine regression models, named: "linear", "quadratic", "cubic", "logistic", "exponential", "power", "monod", "haldane", "logit".

r-nftbart 2.3
Propagated dependencies: r-survival@3.8-3 r-rcpp@1.1.0 r-nnet@7.3-20 r-lattice@0.22-7
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nftbart
Licenses: GPL 2+
Build system: r
Synopsis: Nonparametric Failure Time Bayesian Additive Regression Trees
Description:

Nonparametric Failure Time (NFT) Bayesian Additive Regression Trees (BART): Time-to-event Machine Learning with Heteroskedastic Bayesian Additive Regression Trees (HBART) and Low Information Omnibus (LIO) Dirichlet Process Mixtures (DPM). An NFT BART model is of the form Y = mu + f(x) + sd(x) E where functions f and sd have BART and HBART priors, respectively, while E is a nonparametric error distribution due to a DPM LIO prior hierarchy. See the following for a description of the model at <doi:10.1111/biom.13857>.

r-npmlreg 0.46-5
Propagated dependencies: r-statmod@1.5.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=npmlreg
Licenses: GPL 2+
Build system: r
Synopsis: Nonparametric Maximum Likelihood Estimation for Random Effect Models
Description:

Nonparametric maximum likelihood estimation or Gaussian quadrature for overdispersed generalized linear models and variance component models.

r-nlts 1.0-2
Propagated dependencies: r-locfit@1.5-9.12 r-acepack@1.6.3
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: http://ento.psu.edu/directory/onb1
Licenses: GPL 3
Build system: r
Synopsis: Nonlinear Time Series Analysis
Description:

R functions for (non)linear time series analysis with an emphasis on nonparametric autoregression and order estimation, and tests for linearity / additivity.

r-neuralnettools 1.5.3
Propagated dependencies: r-tidyr@1.3.1 r-scales@1.4.0 r-reshape2@1.4.5 r-nnet@7.3-20 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=NeuralNetTools
Licenses: CC0
Build system: r
Synopsis: Visualization and Analysis Tools for Neural Networks
Description:

Visualization and analysis tools to aid in the interpretation of neural network models. Functions are available for plotting, quantifying variable importance, conducting a sensitivity analysis, and obtaining a simple list of model weights.

r-nestfs 1.0.3
Propagated dependencies: r-proc@1.19.0.1 r-dgof@1.5.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/mcol/nestfs
Licenses: GPL 2 FSDG-compatible
Build system: r
Synopsis: Cross-Validated (Nested) Forward Selection
Description:

Implementation of forward selection based on cross-validated linear and logistic regression.

r-nlt 2.2-2
Propagated dependencies: r-ebayesthresh@1.4-12 r-adlift@1.4-6
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nlt
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Nondecimated Lifting Transform for Signal Denoising
Description:

Uses a modified lifting algorithm on which it builds the nondecimated lifting transform. It has applications in wavelet shrinkage.

r-nflsimulator 0.4.0
Propagated dependencies: r-progress@1.2.3 r-nflfastr@5.1.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/rtelmore/NFLSimulatoR/
Licenses: Expat
Build system: r
Synopsis: Simulating Plays and Drives in the NFL
Description:

The intent here is to enable the simulation of plays/drives and evaluate game-play strategies in the National Football League (NFL). Built-in strategies include going for it on fourth down and varying the proportion of passing/rushing plays during a drive. The user should be familiar with nflscrapR data before trying to write his/her own strategies. This work is inspired by a blog post by Mike Lopez, currently the Director of Data and Analytics at the NFL, Lopez (2019) <https://statsbylopez.netlify.app/post/resampling-nfl-drives/>.

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-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.

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Total results: 68658