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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-nser 1.6.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/nandp1/nser/
Licenses: GPL 3
Build system: r
Synopsis: Bhavcopy and Live Market Data from National Stock Exchange (NSE) & Bombay Stock Exchange (BSE) India
Description:

Download Current & Historical Bhavcopy. Get Live Market data from NSE India of Equities and Derivatives (F&O) segment. Data source <https://www.nseindia.com/>.

r-nac 0.1.0
Propagated dependencies: r-pracma@2.4.6
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://arxiv.org/abs/2306.15616
Licenses: GPL 2
Build system: r
Synopsis: Network-Adjusted Covariates for Community Detection
Description:

Incorporating node-level covariates for community detection has gained increasing attention these years. This package provides the function for implementing the novel community detection algorithm known as Network-Adjusted Covariates for Community Detection (NAC), which is designed to detect latent community structure in graphs with node-level information, i.e., covariates. This algorithm can handle models such as the degree-corrected stochastic block model (DCSBM) with covariates. NAC specifically addresses the discrepancy between the community structure inferred from the adjacency information and the community structure inferred from the covariates information. For more detailed information, please refer to the reference paper: Yaofang Hu and Wanjie Wang (2023) <arXiv:2306.15616>. In addition to NAC, this package includes several other existing community detection algorithms that are compared to NAC in the reference paper. These algorithms are Spectral Clustering On Ratios-of Eigenvectors (SCORE), network-based regularized spectral clustering (Net-based), covariate-based spectral clustering (Cov-based), covariate-assisted spectral clustering (CAclustering) and semidefinite programming (SDP).

r-nimblenobounds 1.0.3
Propagated dependencies: r-nimble@1.4.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/DRJP/nimbleNoBounds
Licenses: Modified BSD
Build system: r
Synopsis: Transformed Distributions for Improved MCMC Efficiency
Description:

This package provides a collection of common univariate bounded probability distributions transformed to the unbounded real line, for the purpose of increased MCMC efficiency.

r-naryn 2.6.32
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://tanaylab.github.io/naryn/
Licenses: Expat
Build system: r
Synopsis: Native Access Medical Record Retriever for High Yield Analytics
Description:

This package provides a toolkit for medical records data analysis. The naryn package implements an efficient data structure for storing medical records, and provides a set of functions for data extraction, manipulation and analysis.

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-naaccr 3.1.1
Propagated dependencies: r-xml@3.99-0.20 r-stringi@1.8.7 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/WerthPADOH/naaccr
Licenses: Expat
Build system: r
Synopsis: Read Cancer Records in the NAACCR Format
Description:

This package provides functions for reading cancer record files which follow a format defined by the North American Association of Central Cancer Registries (NAACCR).

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-nsp 1.0.0
Propagated dependencies: r-lpsolve@5.6.23
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nsp
Licenses: GPL 3+
Build system: r
Synopsis: Inference for Multiple Change-Points in Linear Models
Description:

Implementation of Narrowest Significance Pursuit, a general and flexible methodology for automatically detecting localised regions in data sequences which each must contain a change-point (understood as an abrupt change in the parameters of an underlying linear model), at a prescribed global significance level. Narrowest Significance Pursuit works with a wide range of distributional assumptions on the errors, and yields exact desired finite-sample coverage probabilities, regardless of the form or number of the covariates. For details, see P. Fryzlewicz (2021) <https://stats.lse.ac.uk/fryzlewicz/nsp/nsp.pdf>.

r-nlmixr2rpt 0.2.2
Propagated dependencies: r-yaml@2.3.10 r-xpose-nlmixr2@0.4.1 r-xpose@0.4.23 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-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-nlstac 0.2.0
Propagated dependencies: r-stringr@1.6.0 r-foreach@1.5.2 r-deriv@4.2.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nlstac
Licenses: GPL 3
Build system: r
Synopsis: An R Package for Fitting Separable Nonlinear Models
Description:

Set of functions implementing the algorithm described in Fernandez Torvisco et al. (2018) for fitting separable nonlinear regression curves. See Fernandez Torvisco, Rodriguez-Arias Fernandez and Cabello Sanchez (2018) <doi:10.2298/FIL1812233T>.

r-nparact 0.9.1
Propagated dependencies: r-zoo@1.8-14 r-stringr@1.6.0 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=nparACT
Licenses: GPL 3
Build system: r
Synopsis: Non-Parametric Measures of Actigraphy Data
Description:

Computes interdaily stability (IS), intradaily variability (IV) & the relative amplitude (RA) from actigraphy data as described in Blume et al. (2016) <doi: 10.1016/j.mex.2016.05.006> and van Someren et al. (1999) <doi: 10.3109/07420529908998724>. Additionally, it also computes L5 (i.e. the 5 hours with lowest average actigraphy amplitude) and M10 (the 10 hours with highest average amplitude) as well as the respective start times. The flex versions will also compute the L-value for a user-defined number of minutes. IS describes the strength of coupling of a rhythm to supposedly stable zeitgebers. It varies between 0 (Gaussian Noise) and 1 for perfect IS. IV describes the fragmentation of a rhythm, i.e. the frequency and extent of transitions between rest and activity. It is near 0 for a perfect sine wave, about 2 for Gaussian noise and may be even higher when a definite ultradian period of about 2 hrs is present. RA is the relative amplitude of a rhythm. Note that to obtain reliable results, actigraphy data should cover a reasonable number of days.

r-nblda 1.0.1
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=NBLDA
Licenses: GPL 2+
Build system: r
Synopsis: Negative Binomial Linear Discriminant Analysis
Description:

We proposed a package for the classification task which uses Negative Binomial distribution within Linear Discriminant Analysis (NBLDA). It is an extension of the PoiClaClu package to Negative Binomial distribution. The classification algorithms are based on the papers Dong et al. (2016, ISSN: 1471-2105) and Witten, DM (2011, ISSN: 1932-6157) for NBLDA and PLDA, respectively. Although PLDA is a sparse algorithm and can be used for variable selection, the algorithm proposed by Dong et al. is not sparse. Therefore, it uses all variables in the classifier. Here, we extend Dong et al.'s algorithm to the sparse case by shrinking overdispersion towards 0 (Yu et al., 2013, ISSN: 1367-4803) and offset parameter towards 1 (as proposed by Witten DM, 2011). We support only the classification task with this version.

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-ngbvs 0.3.0
Propagated dependencies: r-rfast@2.1.5.2
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NGBVS
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Variable Selection for SNP Data using Normal-Gamma
Description:

Posterior distribution of case-control fine-mapping. Specifically, Bayesian variable selection for single-nucleotide polymorphism (SNP) data using the normal-gamma prior. Alenazi A.A., Cox A., Juarez M,. Lin W-Y. and Walters, K. (2019) Bayesian variable selection using partially observed categorical prior information in fine-mapping association studies, Genetic Epidemiology. <doi:10.1002/gepi.22213>.

r-nmcalc 0.0.4
Propagated dependencies: r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NMcalc
Licenses: Expat
Build system: r
Synopsis: Basic Calculations for PK/PD Modeling
Description:

Essentials for PK/PD (pharmacokinetics/pharmacodynamics) such as area under the curve, (geometric) coefficient of variation, and other calculations that are not part of base R. This is not a noncompartmental analysis (NCA) package.

r-newsmap 0.9.2
Propagated dependencies: r-stringi@1.8.7 r-quanteda-textstats@0.97.2 r-quanteda@4.3.1 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/koheiw/newsmap
Licenses: Expat
Build system: r
Synopsis: Semi-Supervised Model for Geographical Document Classification
Description:

Semissupervised model for geographical document classification (Watanabe 2018) <doi:10.1080/21670811.2017.1293487>. This package currently contains seed dictionaries in English, German, French, Spanish, Italian, Russian, Hebrew, Arabic, Turkish, Japanese and Chinese (Simplified and Traditional).

r-nnfor 0.9.9
Propagated dependencies: r-uroot@2.1-3 r-tsutils@0.9.4 r-plotrix@3.8-13 r-neuralnet@1.44.2 r-mass@7.3-65 r-glmnet@4.1-10 r-generics@0.1.4 r-forecast@8.24.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://kourentzes.com/forecasting/2019/01/16/tutorial-for-the-nnfor-r-package/
Licenses: GPL 3
Build system: r
Synopsis: Time Series Forecasting with Neural Networks
Description:

Automatic time series modelling with neural networks. Allows fully automatic, semi-manual or fully manual specification of networks. For details of the specification methodology see: (i) Crone and Kourentzes (2010) <doi:10.1016/j.neucom.2010.01.017>; and (ii) Kourentzes et al. (2014) <doi:10.1016/j.eswa.2013.12.011>.

r-npboottprmfbar 0.2.0
Propagated dependencies: r-shiny@1.11.1 r-restriktor@0.6-30 r-npboottprm@0.3.2 r-mmints@0.2.0 r-lmperm@2.1.6 r-fgarch@4052.93 r-dt@0.34.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/mightymetrika/npboottprmFBar
Licenses: Expat
Build system: r
Synopsis: Informative Nonparametric Bootstrap Test with Pooled Resampling
Description:

Sample sizes are often small due to hard to reach target populations, rare target events, time constraints, limited budgets, or ethical considerations. Two statistical methods with promising performance in small samples are the nonparametric bootstrap test with pooled resampling method, which is the focus of Dwivedi, Mallawaarachchi, and Alvarado (2017) <doi:10.1002/sim.7263>, and informative hypothesis testing, which is implemented in the restriktor package. The npboottprmFBar package uses the nonparametric bootstrap test with pooled resampling method to implement informative hypothesis testing. The bootFbar() function can be used to analyze data with this method and the persimon() function can be used to conduct performance simulations on type-one error and statistical power.

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-nblr 0.0.4
Propagated dependencies: r-magrittr@2.0.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/JaseZiv/nblR
Licenses: GPL 3
Build system: r
Synopsis: Data Extraction of Australian NBL Basketball Statistics
Description:

Allow users to obtain basketball statistics for the Australian basketball league NBL'<https://nbl.com.au/>. Stats include play-by-play, shooting locations, results and box scores for teams and players.

r-netda 0.2.0
Propagated dependencies: r-glasso@1.11
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NetDA
Licenses: GPL 2
Build system: r
Synopsis: Network-Based Discriminant Analysis Subject to Multi-Label Classes
Description:

Implementation of discriminant analysis with network structures in predictors accommodated to do classification and prediction.

r-neonplantecology 1.6.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/admahood/neonPlantEcology
Licenses: Expat
Build system: r
Synopsis: Process NEON Plant Data for Ecological Analysis
Description:

Downloading and organizing plant presence and percent cover data from the National Ecological Observatory Network <https://www.neonscience.org>.

r-nopaco 1.0.9
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=nopaco
Licenses: GPL 3+
Build system: r
Synopsis: Non-Parametric Concordance Coefficient
Description:

This package provides a non-parametric test for multi-observer concordance and differences between concordances in (un)balanced data.

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