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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-nestedpp 0.2.0
Propagated dependencies: r-xtable@1.8-4 r-reshape2@1.4.5 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=nestedpp
Licenses: GPL 3
Build system: r
Synopsis: Performance Profiles and Nested Performance Profiles
Description:

Library to plot performance profiles (Dolan and More (2002) <doi:10.1007/s101070100263>) and nested performance profiles (Hekmati and Mirhajianmoghadam (2019) <doi:10.19139/soic-2310-5070-679>) for a given data frame.

r-nlmeu 0.71.7
Propagated dependencies: r-nlme@3.1-168
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/agalecki/nlmeU
Licenses: GPL 2
Build system: r
Synopsis: Functions and Data Supporting 'Linear Mixed-Effects Models: A Step-by-Step Approach'
Description:

This package provides functions and datasets to support the book by Galecki and Burzykowski (2013), Linear Mixed-Effects Models: A Step-by-Step Approach', Springer. Includes functions for power calculations, log-likelihood contributions, and data simulation for linear mixed-effects models.

r-nmaoutlier 0.2.1
Propagated dependencies: r-reshape2@1.4.5 r-netmeta@3.3-1 r-meta@8.2-1 r-mass@7.3-65 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://github.com/petropouloumaria/NMAoutlier
Licenses: GPL 2+
Build system: r
Synopsis: Detecting Outliers in Network Meta-Analysis
Description:

This package provides a set of functions providing several outlier (i.e., studies with extreme findings) and influential detection measures and methodologies in network meta-analysis : - simple outlier and influential detection measures - outlier and influential detection measures by considering study deletion (shift the mean) - plots for outlier and influential detection measures - Q-Q plot for network meta-analysis - Forward Search algorithm in network meta-analysis. - forward plots to monitor statistics in each step of the forward search algorithm - forward plots for summary estimates and their confidence intervals in each step of forward search algorithm.

r-nomesbr 0.0.9
Propagated dependencies: r-tictoc@1.2.1 r-stringr@1.6.0 r-httr2@1.2.1 r-dplyr@1.1.4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/ipeadata-lab/nomesbr
Licenses: Expat
Build system: r
Synopsis: Limpa e Simplifica Nomes de Pessoas (Name Cleaner and Simplifier)
Description:

Limpa e simplifica nomes de pessoas para auxiliar no pareamento de banco de dados na ausência de chaves únicas não ambà guas. Detecta e corrige erros tipográficos mais comuns, simplifica opcionalmente termos sujeitos eventualmente a omissão em cadastros, e simplifica foneticamente suas palavras, aplicando variação própria do algoritmo metaphoneBR. (Cleans and simplifies person names to assist in database matching when unambiguous unique keys are unavailable. Detects and corrects common typos, optionally simplifies terms prone to omission in records, and applies phonetic simplification using a custom variation of the metaphoneBR algorithm.) Mation (2025) <doi:10.6082/uchicago.15104>.

r-notionr 0.0.9
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: <https://www.enelmargen.org/notionR/>
Licenses: Expat
Build system: r
Synopsis: R Wrapper for 'Notion' API
Description:

This package provides functions to query databases and notes in Notion', using the official REST API. To learn more about the functionality of the Notion API, see <https://developers.notion.com/>.

r-netplot 0.3-0
Propagated dependencies: r-sna@2.8 r-network@1.19.0 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/USCCANA/netplot
Licenses: Expat
Build system: r
Synopsis: Beautiful Graph Drawing
Description:

This package provides a graph visualization engine that emphasizes on aesthetics at the same time providing default parameters that yield out-of-the-box-nice visualizations. The package is built on top of The Grid Graphics Package and seamlessly work with igraph and network objects.

r-nonmem2rx 0.1.9
Propagated dependencies: r-xml2@1.5.0 r-rxode2@5.0.1 r-rcpp@1.1.0 r-qs2@0.1.6 r-magrittr@2.0.4 r-lotri@1.0.2 r-ggplot2@4.0.1 r-ggforce@0.5.0 r-dparser@1.3.1-13 r-digest@0.6.39 r-data-table@1.17.8 r-crayon@1.5.3 r-cli@3.6.5 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://nlmixr2.github.io/nonmem2rx/
Licenses: GPL 3+
Build system: r
Synopsis: Converts 'NONMEM' Models to 'rxode2'
Description:

NONMEM has been a tool for running nonlinear mixed effects models since the 80s and is still used today (Bauer 2019 <doi:10.1002/psp4.12404>). This tool allows you to convert NONMEM models to rxode2 (Wang, Hallow and James (2016) <doi:10.1002/psp4.12052>) and with simple models nlmixr2 syntax (Fidler et al (2019) <doi:10.1002/psp4.12445>). The nlmixr2 syntax requires the residual specification to be included and it is not always translated. If available, the rxode2 model will read in the NONMEM data and compare the simulation for the population model ('PRED') individual model ('IPRED') and residual model ('IWRES') to immediately show how well the translation is performing. This saves the model development time for people who are creating an rxode2 model manually. Additionally, this package reads in all the information to allow simulation with uncertainty (that is the number of observations, the number of subjects, and the covariance matrix) with a rxode2 model. This is complementary to the babelmixr2 package that translates nlmixr2 models to NONMEM and can convert the objects converted from nonmem2rx to a full nlmixr2 fit.

r-nltm 1.4.6
Propagated dependencies: r-survival@3.8-3
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/mclements/nltm
Licenses: GPL 2
Build system: r
Synopsis: Non-Linear Transformation Models
Description:

Fits a non-linear transformation model ('nltm') for analyzing survival data, see Tsodikov (2003) <doi:10.1111/1467-9868.00414>. The class of nltm includes the following currently supported models: Cox proportional hazard, proportional hazard cure, proportional odds, proportional hazard - proportional hazard cure, proportional hazard - proportional odds cure, Gamma frailty, and proportional hazard - proportional odds.

r-nlints 1.4.6
Propagated dependencies: r-timeseries@4041.111 r-rdpack@2.6.4 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NlinTS
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Models for Non Linear Causality Detection in Time Series
Description:

Models for non-linear time series analysis and causality detection. The main functionalities of this package consist of an implementation of the classical causality test (C.W.J.Granger 1980) <doi:10.1016/0165-1889(80)90069-X>, and a non-linear version of it based on feed-forward neural networks. This package contains also an implementation of the Transfer Entropy <doi:10.1103/PhysRevLett.85.461>, and the continuous Transfer Entropy using an approximation based on the k-nearest neighbors <doi:10.1103/PhysRevE.69.066138>. There are also some other useful tools, like the VARNN (Vector Auto-Regressive Neural Network) prediction model, the Augmented test of stationarity, and the discrete and continuous entropy and mutual information.

r-nmvanova 1.1.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NMVANOVA
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Novice Model Variation ANOVA
Description:

Due to Rstudio's status as open source software, we believe it will be utilized frequently for future data analysis by users whom lack formal training or experience with R'. The NMVANOVA (Novice Model Variation ANOVA) a streamlined variation of experimental design functions that allows novice Rstudio users to perform different model variations one-way analysis of variance without downloading multiple libraries or packages. Users can easily manipulate the data block, and needed inputs so that users only have to plugin the four designed variables/values.

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-netmediate 1.1.1
Propagated dependencies: r-vgam@1.1-13 r-tergm@4.2.2 r-sna@2.8 r-rsiena@1.5.0 r-plyr@1.8.9 r-plm@2.6-7 r-network@1.19.0 r-mass@7.3-65 r-lme4@1.1-37 r-intergraph@2.0-4 r-gam@1.22-6 r-ergmargins@1.6.1 r-ergm@4.12.0 r-btergm@1.11.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=netmediate
Licenses: GPL 2+
Build system: r
Synopsis: Micro-Macro Analysis for Social Networks
Description:

Estimates micro effects on macro structures (MEMS) and average micro mediated effects (AMME). URL: <https://github.com/sduxbury/netmediate>. BugReports: <https://github.com/sduxbury/netmediate/issues>. Robins, Garry, Phillipa Pattison, and Jodie Woolcock (2005) <doi:10.1086/427322>. Snijders, Tom A. B., and Christian E. G. Steglich (2015) <doi:10.1177/0049124113494573>. Imai, Kosuke, Luke Keele, and Dustin Tingley (2010) <doi:10.1037/a0020761>. Duxbury, Scott (2023) <doi:10.1177/00811750231209040>. Duxbury, Scott (2024) <doi:10.1177/00811750231220950>.

r-npcox 1.3
Propagated dependencies: r-progress@1.2.3
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NPCox
Licenses: GPL 3
Build system: r
Synopsis: Nonparametric and Semiparametric Proportional Hazards Model
Description:

An estimation procedure for the analysis of nonparametric proportional hazards model (e.g. h(t) = h0(t)exp(b(t)'Z)), providing estimation of b(t) and its pointwise standard errors, and semiparametric proportional hazards model (e.g. h(t) = h0(t)exp(b(t)'Z1 + c*Z2)), providing estimation of b(t), c and their standard errors. More details can be found in Lu Tian et al. (2005) <doi:10.1198/016214504000000845>.

r-nhs-predict 1.4.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nhs.predict
Licenses: GPL 2
Build system: r
Synopsis: Breast Cancer Survival and Therapy Benefits
Description:

Calculate Overall Survival or Recurrence-Free Survival for breast cancer patients, using NHS Predict'. The time interval for the estimation can be set up to 15 years, with default at 10. Incremental therapy benefits are estimated for hormone therapy, chemotherapy, trastuzumab, and bisphosphonates. An additional function, suited for SCAN audits, features a more user-friendly version of the code, with fewer inputs, but necessitates the correct standardised inputs. This work is not affiliated with the development of NHS Predict and its underlying statistical model. Details on NHS Predict can be found at: <doi:10.1186/bcr2464>. The web version of NHS Predict': <https://breast.predict.nhs.uk/>. A small dataset of 50 fictional patient observations is provided for the purpose of running examples with the main two functions, and an additional dataset is provided for running example with the dedicated SCAN function.

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-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-nextgenshinyapps 2.1
Propagated dependencies: r-shiny@1.11.1 r-quickcode@1.0.8 r-htmltools@0.5.8.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://nextgenshinyapps.obi.obianom.com
Licenses: Expat
Build system: r
Synopsis: Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Description:

Novel responsive tools for developing R based Shiny dashboards and applications. The scripts and style sheets are based on jQuery <https://jquery.com/> and Bootstrap <https://getbootstrap.com/>.

r-networkabc 0.9-1
Propagated dependencies: r-sna@2.8 r-rcolorbrewer@1.1-3 r-network@1.19.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://fbertran.github.io/networkABC/
Licenses: GPL 3
Build system: r
Synopsis: Network Reverse Engineering with Approximate Bayesian Computation
Description:

We developed an inference tool based on approximate Bayesian computation to decipher network data and assess the strength of the inferred links between network's actors. It is a new multi-level approximate Bayesian computation (ABC) approach. At the first level, the method captures the global properties of the network, such as a scale-free structure and clustering coefficients, whereas the second level is targeted to capture local properties, including the probability of each couple of genes being linked. Up to now, Approximate Bayesian Computation (ABC) algorithms have been scarcely used in that setting and, due to the computational overhead, their application was limited to a small number of genes. On the contrary, our algorithm was made to cope with that issue and has low computational cost. It can be used, for instance, for elucidating gene regulatory network, which is an important step towards understanding the normal cell physiology and complex pathological phenotype. Reverse-engineering consists in using gene expressions over time or over different experimental conditions to discover the structure of the gene network in a targeted cellular process. The fact that gene expression data are usually noisy, highly correlated, and have high dimensionality explains the need for specific statistical methods to reverse engineer the underlying network.

r-networktools 1.6.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://CRAN.R-project.org/package=networktools
Licenses: GPL 3
Build system: r
Synopsis: Tools for Identifying Important Nodes in Networks
Description:

Includes assorted tools for network analysis. Bridge centrality; goldbricker; MDS, PCA, & eigenmodel network plotting.

r-nlsr 2023.8.31
Propagated dependencies: r-digest@0.6.39
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nlsr
Licenses: GPL 2
Build system: r
Synopsis: Functions for Nonlinear Least Squares Solutions - Updated 2022
Description:

This package provides tools for working with nonlinear least squares problems. For the estimation of models reliable and robust tools than nls(), where the the Gauss-Newton method frequently stops with singular gradient messages. This is accomplished by using, where possible, analytic derivatives to compute the matrix of derivatives and a stabilization of the solution of the estimation equations. Tools for approximate or externally supplied derivative matrices are included. Bounds and masks on parameters are handled properly.

r-networksem 0.4
Propagated dependencies: r-sna@2.8 r-network@1.19.0 r-lavaan@0.6-20 r-latentnet@2.12.0 r-influential@2.3.0 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=networksem
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Network Structural Equation Modeling
Description:

Several methods have been developed to integrate structural equation modeling techniques with network data analysis to examine the relationship between network and non-network data. Both node-based and edge-based information can be extracted from the network data to be used as observed variables in structural equation modeling. To facilitate the application of these methods, model specification can be performed in the familiar syntax of the lavaan package, ensuring ease of use for researchers. Technical details and examples can be found at <https://bigsem.psychstat.org>.

r-ncutyx 0.1.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/Seborinos/NCutYX
Licenses: GPL 3
Build system: r
Synopsis: Clustering of Omics Data of Multiple Types with a Multilayer Network Representation
Description:

Omics data come in different forms: gene expression, methylation, copy number, protein measurements and more. NCutYX allows clustering of variables, of samples, and both variables and samples (biclustering), while incorporating the dependencies across multiple types of Omics data. (SJ Teran Hidalgo et al (2017), <doi:10.1186/s12864-017-3990-1>).

r-nlsmsn 0.0-6
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nlsmsn
Licenses: GPL 3+
Build system: r
Synopsis: Fitting Nonlinear Models with Scale Mixture of Skew-Normal Distributions
Description:

Fit univariate non-linear scale mixture of skew-normal(NL-SMSN) regression, details in Garay, Lachos and Abanto-Valle (2011) <doi:10.1016/j.jkss.2010.08.003> and Lachos, Bandyopadhyay and Garay (2011) <doi:10.1016/j.spl.2011.03.019>.

r-nflfastr 5.2.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://nflfastr.com/
Licenses: Expat
Build system: r
Synopsis: Functions to Efficiently Access NFL Play by Play Data
Description:

This package provides a set of functions to access National Football League play-by-play data from <https://www.nfl.com/>.

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