_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
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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-newscatcher 0.1.2
Propagated dependencies: r-tidyrss@2.0.7
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/discindo/newscatcheR/
Licenses: Expat
Build system: r
Synopsis: Programmatically Collect Normalized News from (Almost) Any Website
Description:

Programmatically collect normalized news from (almost) any website. An R clone of the <https://github.com/kotartemiy/newscatcher> Python module.

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-netdose 0.7-4
Propagated dependencies: r-tidyr@1.3.1 r-netmeta@3.3-1 r-meta@8.2-1 r-matrix@1.7-4 r-mass@7.3-65 r-hmisc@5.2-4 r-ggplot2@4.0.1 r-ggh4x@0.3.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/petropouloumaria/netdose
Licenses: GPL 2+
Build system: r
Synopsis: Dose-Response Network Meta-Analysis in a Frequentist Way
Description:

This package provides a set of functions providing the implementation of the network meta-analysis model with dose-response relationships, predicted values of the fitted model and dose-response plots in a frequentist way.

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-nifti-pbcor 1.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nifti.pbcor
Licenses: FSDG-compatible
Build system: r
Synopsis: Parcel-Based Correlation Between NIfTI Images
Description:

Estimate the correlation between two NIfTI images across random parcellations of the images (Fortea et al., under review). This approach overcomes the problems of both voxel-based correlations (neighbor voxels may be spatially dependent) and atlas-based correlations (the correlation may depend on the atlas used).

r-nda 0.2.4
Propagated dependencies: r-visnetwork@2.1.4 r-rfast@2.1.5.2 r-psych@2.5.6 r-ppcor@1.1 r-metrics@0.1.4 r-mco@1.17 r-matrix@1.7-4 r-mass@7.3-65 r-lm-beta@1.7-3 r-leidenalg@1.1.5 r-igraph@2.2.1 r-energy@1.7-12
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/kzst/nda
Licenses: GPL 2+
Build system: r
Synopsis: Generalized Network-Based Dimensionality Reduction and Analysis
Description:

Non-parametric dimensionality reduction function. Reduction with and without feature selection. Plot functions. Automated feature selections. Kosztyan et. al. (2024) <doi:10.1016/j.eswa.2023.121779>.

r-nifti-io 1.0.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nifti.io
Licenses: Expat
Build system: r
Synopsis: Read and Write NIfTI Files
Description:

This package provides tools for reading and writing NIfTI-1.1 (NII) files, including optimized voxelwise read/write operations and a simplified method to write dataframes to NII. Specification of the NIfTI-1.1 format can be found here <https://nifti.nimh.nih.gov/nifti-1>. Scientific publication first using these tools Koscik TR, Man V, Jahn A, Lee CH, Cunningham WA (2020) <doi:10.1016/j.neuroimage.2020.116764> "Decomposing the neural pathways in a simple, value-based choice." Neuroimage, 214, 116764.

r-networkdynamic 0.11.5
Propagated dependencies: r-statnet-common@4.12.0 r-networklite@1.1.0 r-network@1.19.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://statnet.org/
Licenses: GPL 3
Build system: r
Synopsis: Dynamic Extensions for Network Objects
Description:

Simple interface routines to facilitate the handling of network objects with complex intertemporal data. This is a part of the "statnet" suite of packages for network analysis.

r-nsr 0.1.0
Propagated dependencies: r-jsonlite@2.0.0 r-httr@1.4.7
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NSR
Licenses: Expat
Build system: r
Synopsis: 'Native Status Resolver'
Description:

This package provides access to the Native Status Resolver (NSR) <https://github.com/ojalaquellueva/nsr> API through R. The user supplies plant taxonomic names and political divisions and the package returns information about their likely native status (e.g., native, non-native,endemic), along with information on how those decisions were made.

r-navigatr 0.2.1
Propagated dependencies: r-vctrs@0.6.5 r-tidyselect@1.2.1 r-stickyr@0.1.2 r-rlang@1.1.6 r-purrr@1.2.0 r-pillar@1.11.1 r-lifecycle@1.0.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/UchidaMizuki/navigatr
Licenses: Expat
Build system: r
Synopsis: Navigation Menu for Pipe-Friendly Data Processing
Description:

This package provides a navigation menu to enable pipe-friendly data processing for hierarchical data structures. By activating the menu items, you can perform operations on each item while maintaining the overall structure in attributes.

r-nascar-data 2.2.3
Propagated dependencies: r-stringr@1.6.0 r-stringdist@0.9.15 r-rvest@1.0.5 r-rlang@1.1.6 r-purrr@1.2.0 r-glue@1.8.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://www.kyleGrealis.com/nascaR.data/
Licenses: GPL 3+
Build system: r
Synopsis: NASCAR Race Data
Description:

This package provides a collection of NASCAR race, driver, owner and manufacturer data across the three major NASCAR divisions: NASCAR Cup Series, NASCAR Xfinity Series, and NASCAR Craftsman Truck Series. The curated data begins with the 1949 season and extends through the end of the 2024 season. Explore race, season, or career performance for drivers, teams, and manufacturers throughout NASCAR's history. Data was sourced with permission from DriverAverages.com.

r-nawtilus 0.1.4
Propagated dependencies: r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nawtilus
Licenses: GPL 3
Build system: r
Synopsis: Navigated Weighting for the Inverse Probability Weighting
Description:

This package implements the navigated weighting (NAWT) proposed by Katsumata (2020) <arXiv:2005.10998>, which improves the inverse probability weighting by utilizing estimating equations suitable for a specific pre-specified parameter of interest (e.g., the average treatment effects or the average treatment effects on the treated) in propensity score estimation. It includes the covariate balancing propensity score proposed by Imai and Ratkovic (2014) <doi:10.1111/rssb.12027>, which uses covariate balancing conditions in propensity score estimation. The point estimate of the parameter of interest as well as coefficients for propensity score estimation and their uncertainty are produced using the M-estimation. The same functions can be used to estimate average outcomes in missing outcome cases.

r-nhldata 1.0.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NHLData
Licenses: CC0
Build system: r
Synopsis: Scores for Every Season Since the Founding of the NHL in 1917
Description:

Each dataset contains scores for every game during a specific season of the NHL.

r-nphrct 0.1.1
Propagated dependencies: r-survival@3.8-3 r-purrr@1.2.0 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=nphRCT
Licenses: GPL 3+
Build system: r
Synopsis: Non-Proportional Hazards in Randomized Controlled Trials
Description:

Perform a stratified weighted log-rank test in a randomized controlled trial. Tests can be visualized as a difference in average score on the two treatment arms. These methods are described in Magirr and Burman (2018) <doi:10.48550/arXiv.1807.11097>, Magirr (2020) <doi:10.48550/arXiv.2007.04767>, and Magirr and Jimenez (2022) <doi:10.48550/arXiv.2201.10445>.

r-neojags 0.1.6
Propagated dependencies: r-runjags@2.2.2-5 r-rjags@4-17 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/madsyair/neojags
Licenses: GPL 2
Build system: r
Synopsis: Neo-Normal Distributions Family for Markov Chain Monte Carlo (MCMC) Models in 'JAGS'
Description:

This package provides a JAGS extension module provides neo-normal distributions family including MSNBurr, MSNBurr-IIa, GMSNBurr, Lunetta Exponential Power, Fernandez-Steel Skew t, Fernandez-Steel Skew Normal, Fernandez-Osiewalski-Steel Skew Exponential Power, Jones Skew Exponential Power. References: Choir, A. S. (2020). "The New Neo-Normal Distributions and Their Properties".Unpublished Dissertation. Denwood, M.J. (2016) <doi:10.18637/jss.v071.i09>. Fernandez, C., Osiewalski, J., & Steel, M. F. (1995) <doi:10.1080/01621459.1995.10476637>. Fernandez, C., & Steel, M. F. (1998) <doi:10.1080/01621459.1998.10474117>. Iriawan, N. (2000). "Computationally Intensive Approaches to Inference in NeoNormal Linear Models".Unpublished Dissertation. Mineo, A., & Ruggieri, M. (2005) <doi:10.18637/jss.v012.i04>. Rigby, R. A., & Stasinopoulos, D. M. (2005) <doi:10.1111/j.1467-9876.2005.00510.x>. Lunetta, G. (1963). "Di una Generalizzazione dello Schema della Curva Normale". Rigby, R. A., Stasinopoulos, M. D., Heller, G. Z., & Bastiani, F. D. (2019) <doi:10.1201/9780429298547>.

r-npboottprm 0.3.2
Propagated dependencies: r-sn@2.1.1 r-shinythemes@1.2.0 r-shiny@1.11.1 r-mmints@0.2.0 r-mkinfer@1.3 r-mass@7.3-65 r-lmperm@2.1.6 r-ggplot2@4.0.1 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/npboottprm
Licenses: Expat
Build system: r
Synopsis: Nonparametric Bootstrap Test with Pooled Resampling
Description:

Addressing crucial research questions often necessitates a small sample size due to factors such as distinctive target populations, rarity of the event under study, time and cost constraints, ethical concerns, or group-level unit of analysis. Many readily available analytic methods, however, do not accommodate small sample sizes, and the choice of the best method can be unclear. The npboottprm package enables the execution of nonparametric bootstrap tests with pooled resampling to help fill this gap. Grounded in the statistical methods for small sample size studies detailed in Dwivedi, Mallawaarachchi, and Alvarado (2017) <doi:10.1002/sim.7263>, the package facilitates a range of statistical tests, encompassing independent t-tests, paired t-tests, and one-way Analysis of Variance (ANOVA) F-tests. The nonparboot() function undertakes essential computations, yielding detailed outputs which include test statistics, effect sizes, confidence intervals, and bootstrap distributions. Further, npboottprm incorporates an interactive shiny web application, nonparboot_app(), offering intuitive, user-friendly data exploration.

r-ngchm 1.0.4
Propagated dependencies: r-tsvio@1.0.6 r-logger@0.4.1 r-jsonlite@2.0.0 r-httr@1.4.7 r-htmltools@0.5.8.1 r-digest@0.6.39
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://md-anderson-bioinformatics.github.io/NGCHM-R/
Licenses: GPL 3
Build system: r
Synopsis: Next Generation Clustered Heat Maps
Description:

Next-Generation Clustered Heat Maps (NG-CHMs) allow for dynamic exploration of heat map data in a web browser. NGCHM allows users to create both stand-alone HTML files containing a Next-Generation Clustered Heat Map, and .ngchm files to view in the NG-CHM viewer. See Ryan MC, Stucky M, et al (2020) <doi:10.12688/f1000research.20590.2> for more details.

r-npwbs 0.2.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=npwbs
Licenses: GPL 3
Build system: r
Synopsis: Nonparametric Multiple Change Point Detection Using WBS
Description:

This package implements the procedure from G. J. Ross (2021) - "Nonparametric Detection of Multiple Location-Scale Change Points via Wild Binary Segmentation" <arxiv:2107.01742>. This uses a version of Wild Binary Segmentation to detect multiple location-scale (i.e. mean and/or variance) change points in a sequence of univariate observations, with a strict control on the probability of incorrectly detecting a change point in a sequence which does not contain any.

r-ncappc 1.0.0
Propagated dependencies: r-xtable@1.8-4 r-tidyr@1.3.1 r-tibble@3.3.0 r-scales@1.4.0 r-rmarkdown@2.30 r-rlang@1.1.6 r-reshape2@1.4.5 r-readr@2.1.6 r-purrr@1.2.0 r-poped@0.7.0 r-magrittr@2.0.4 r-lazyeval@0.2.2 r-knitr@1.50 r-gtable@0.3.6 r-gridextra@2.3 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-bookdown@0.45
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/UUPharmacometrics/ncappc
Licenses: GPL 3
Build system: r
Synopsis: NCA Calculations and Population Model Diagnosis
Description:

This package provides a flexible tool that can perform (i) traditional non-compartmental analysis (NCA) and (ii) Simulation-based posterior predictive checks for population pharmacokinetic (PK) and/or pharmacodynamic (PKPD) models using NCA metrics. The methods are described in Acharya et al. (2016) <doi:10.1016/j.cmpb.2016.01.013>.

r-nsrfa 0.7-17
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nsRFA
Licenses: GPL 2+
Build system: r
Synopsis: Non-Supervised Regional Frequency Analysis
Description:

This package provides a collection of statistical tools for objective (non-supervised) applications of the Regional Frequency Analysis methods in hydrology. The package refers to the index-value method and, more precisely, helps the hydrologist to: (1) regionalize the index-value; (2) form homogeneous regions with similar growth curves; (3) fit distribution functions to the empirical regional growth curves. Most of the methods are those described in the Flood Estimation Handbook (Centre for Ecology & Hydrology, 1999, ISBN:9781906698003). Homogeneity tests from Hosking and Wallis (1993) <doi:10.1029/92WR01980> and Viglione et al. (2007) <doi:10.1029/2006WR005095> are available.

r-nlpclient 1.0
Propagated dependencies: r-xml2@1.5.0 r-nlp@0.3-2 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=NLPclient
Licenses: GPL 2
Build system: r
Synopsis: Stanford 'CoreNLP' Annotation Client
Description:

Stanford CoreNLP annotation client. Stanford CoreNLP <https://stanfordnlp.github.io/CoreNLP/index.html> integrates all NLP tools from the Stanford Natural Language Processing Group, including a part-of-speech (POS) tagger, a named entity recognizer (NER), a parser, and a coreference resolution system, and provides model files for the analysis of English. More information can be found in the README.

r-nbpinference 1.0.3
Propagated dependencies: r-rdpack@2.6.4 r-nbpmatching@1.5.6
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://github.com/AnthonyFrazierCSU/nbpInference
Licenses: GPL 3+
Build system: r
Synopsis: Inference on Average Treatment Effects for Continuous Treatments
Description:

Conduct inference on the sample average treatment effect for a matched (observational) dataset with a continuous treatment. Equipped with calipered non-bipartite matching, bias-corrected sample average treatment effect estimation, and covariate-adjusted variance estimation. Matching, estimation, and inference methods are described in Frazier, Heng and Zhou (2024) <doi:10.48550/arXiv.2409.11701>.

r-nonmemica 1.0.11
Propagated dependencies: r-xml2@1.5.0 r-tidyr@1.3.1 r-spec@0.1.9 r-rlang@1.1.6 r-metaplot@0.8.4 r-magrittr@2.0.4 r-lazyeval@0.2.2 r-encode@0.3.6 r-dplyr@1.1.4 r-csv@0.6.2
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=nonmemica
Licenses: GPL 3
Build system: r
Synopsis: Create and Evaluate NONMEM Models in a Project Context
Description:

Systematically creates and modifies NONMEM(R) control streams. Harvests NONMEM output, builds run logs, creates derivative data, generates diagnostics. NONMEM (ICON Development Solutions <https://www.iconplc.com/>) is software for nonlinear mixed effects modeling. See package?nonmemica'.

r-npcp 0.2-6
Propagated dependencies: r-sandwich@3.1-1
Channel: guix-cran
Location: guix-cran/packages/n.scm (guix-cran packages n)
Home page: https://cran.r-project.org/package=npcp
Licenses: GPL 3+ FSDG-compatible
Build system: r
Synopsis: Some Nonparametric CUSUM Tests for Change-Point Detection in Possibly Multivariate Observations
Description:

This package provides nonparametric CUSUM tests for detecting changes in possibly serially dependent univariate or low-dimensional multivariate observations. Retrospective tests sensitive to changes in the expectation, the variance, the covariance, the autocovariance, the distribution function, Spearman's rho, Kendall's tau, Gini's mean difference, and the copula are provided, as well as a test for detecting changes in the distribution of independent block maxima (with environmental studies in mind). The package also contains a test sensitive to changes in the autocopula and a combined test of stationarity sensitive to changes in the distribution function and the autocopula. The latest additions are an open-end sequential test based on the retrospective CUSUM statistic that can be used for monitoring changes in the mean of possibly serially dependent univariate observations, as well as closed-end and open-end sequential tests based on empirical distribution functions that can be used for monitoring changes in the contemporary distribution of possibly serially dependent univariate or low-dimensional multivariate observations.

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