_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
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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-sftools 0.1.0
Propagated dependencies: r-wordspace@0.2-9 r-ff@4.5.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://sites.google.com/site/mohamedlaibwebpage/
Licenses: GPL 3
Build system: r
Synopsis: Space Filling Based Tools for Data Mining
Description:

This package contains space filling based tools for machine learning and data mining. Some functions offer several computational techniques and deal with the out of memory for large big data by using the ff package.

r-skewhyperbolic 0.4-2
Propagated dependencies: r-generalizedhyperbolic@0.8-7 r-distributionutils@0.6-2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://r-forge.r-project.org/projects/rmetrics/
Licenses: GPL 2+
Build system: r
Synopsis: The Skew Hyperbolic Student t-Distribution
Description:

This package provides functions are provided for the density function, distribution function, quantiles and random number generation for the skew hyperbolic t-distribution. There are also functions that fit the distribution to data. There are functions for the mean, variance, skewness, kurtosis and mode of a given distribution and to calculate moments of any order about any centre. To assess goodness of fit, there are functions to generate a Q-Q plot, a P-P plot and a tail plot.

r-steiniv 0.1-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SteinIV
Licenses: GPL 2+
Build system: r
Synopsis: Semi-Parametric Stein-Like Estimator with Instrumental Variables
Description:

Routines for computing different types of linear estimators, based on instrumental variables (IVs), including the semi-parametric Stein-like (SPS) estimator, originally introduced by Judge and Mittelhammer (2004) <DOI:10.1198/016214504000000430>.

r-stlnpp 0.5.0
Propagated dependencies: r-spatstat-univar@3.1-5 r-spatstat-random@3.4-3 r-spatstat-linnet@3.3-2 r-spatstat-geom@3.6-1 r-spatstat-explore@3.6-0 r-spatstat@3.4-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=stlnpp
Licenses: GPL 2+
Build system: r
Synopsis: Spatio-Temporal Analysis of Point Patterns on Linear Networks
Description:

Statistical analysis of spatio-temporal point processes on linear networks. This packages provides tools to visualise and analyse spatio-temporal point patterns on linear networks using first, second, and higher-order summary statistics.

r-sss 0.2.2
Propagated dependencies: r-xml2@1.5.0 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: http://andrie.github.io/sss/
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Import Files in the Triple-s (Standard Survey Structure) Format
Description:

This package provides tools to import survey files in the .sss (triple-s) format. The package provides the function read.sss() that reads the .asc (or .csv') and .sss files of a triple-s survey data file. See also <https://triple-s.org/>.

r-semnar 0.8.2
Propagated dependencies: r-urlshortener@2.0.0 r-parsedate@1.3.2 r-lubridate@1.9.4 r-leaflet@2.2.3 r-jsonlite@2.0.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=semnar
Licenses: GPL 3
Build system: r
Synopsis: Constructing and Interacting with Databases of Presentations
Description:

This package provides methods for constructing and maintaining a database of presentations in R. The presentations are either ones that the user gives or gave or presentations at a particular event or event series. The package also provides a plot method for the interactive mapping of the presentations using leaflet by grouping them according to country, city, year and other presentation attributes. The markers on the map come with popups providing presentation details (title, institution, event, links to materials and events, and so on).

r-sparkhail 0.1.1
Propagated dependencies: r-sparklyr-nested@0.0.4 r-sparklyr@1.9.3 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sparkhail
Licenses: ASL 2.0 FSDG-compatible
Build system: r
Synopsis: 'Sparklyr' Extension for 'Hail'
Description:

Hail is an open-source, general-purpose, python based data analysis tool with additional data types and methods for working with genomic data, see <https://hail.is/>. Hail is built to scale and has first-class support for multi-dimensional structured data, like the genomic data in a genome-wide association study (GWAS). Hail is exposed as a python library, using primitives for distributed queries and linear algebra implemented in scala', spark', and increasingly C++'. The sparkhail is an R extension using sparklyr package. The idea is to help R users to use hail functionalities with the well-know tidyverse syntax, see <https://www.tidyverse.org/>.

r-sorocs 0.1.0
Propagated dependencies: r-mvtnorm@1.3-3 r-mcmcpack@1.7-1 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: http://github.com/wzhang17/sorocs.git
Licenses: GPL 3
Build system: r
Synopsis: Bayesian Semiparametric Approach to Correlated ROC Surfaces
Description:

This package provides a Bayesian semiparametric Dirichlet process mixtures to estimate correlated receiver operating characteristic (ROC) surfaces and the associated volume under the surface (VUS) with stochastic order constraints. The reference paper is:Zhen Chen, Beom Seuk Hwang, (2018) "A Bayesian semiparametric approach to correlated ROC surfaces with stochastic order constraints". Biometrics, 75, 539-550. <doi:10.1111/biom.12997>.

r-setwidth 1.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=setwidth
Licenses: GPL 2+
Build system: r
Synopsis: Automatically Set the Width Option on Terminal Emulators
Description:

Automatically sets the value of options("width") when the terminal emulator is resized. The functions of this package only work if R is compiled for Unix systems and it is running interactively in a terminal emulator.

r-sams 0.4.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sams
Licenses: GPL 3
Build system: r
Synopsis: Merge-Split Samplers for Conjugate Bayesian Nonparametric Models
Description:

Markov chain Monte Carlo samplers for posterior simulations of conjugate Bayesian nonparametric mixture models. Functionality is provided for Gibbs sampling as in Algorithm 3 of Neal (2000) <DOI:10.1080/10618600.2000.10474879>, restricted Gibbs merge-split sampling as described in Jain & Neal (2004) <DOI:10.1198/1061860043001>, and sequentially-allocated merge-split sampling <DOI:10.1080/00949655.2021.1998502>, as well as summary and utility functions.

r-spatialvs 1.1
Propagated dependencies: r-nlme@3.1-168 r-mass@7.3-65 r-fields@17.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SpatialVS
Licenses: GPL 2
Build system: r
Synopsis: Spatial Variable Selection
Description:

Perform variable selection for the spatial Poisson regression model under the adaptive elastic net penalty. Spatial count data with covariates is the input. We use a spatial Poisson regression model to link the spatial counts and covariates. For maximization of the likelihood under adaptive elastic net penalty, we implemented the penalized quasi-likelihood (PQL) and the approximate penalized loglikelihood (APL) methods. The proposed methods can automatically select important covariates, while adjusting for possible spatial correlations among the responses. More details are available in Xie et al. (2018, <arXiv:1809.06418>). The package also contains the Lyme disease dataset, which consists of the disease case data from 2006 to 2011, and demographic data and land cover data in Virginia. The Lyme disease case data were collected by the Virginia Department of Health. The demographic data (e.g., population density, median income, and average age) are from the 2010 census. Land cover data were obtained from the Multi-Resolution Land Cover Consortium for 2006.

r-seasonalytics 0.1.0
Propagated dependencies: r-seastests@0.15.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=seasonalytics
Licenses: GPL 3
Build system: r
Synopsis: Compute Seasonality Index, Seasonalized and Deseaonalised the Time Series Data
Description:

The computation of a seasonal index is a fundamental step in time-series forecasting when the data exhibits seasonality. Specifically, a seasonal index quantifies â for each season (e.g. month, quarter, week) â the relative magnitude of the seasonal effect compared to the overall average level of the series. This package has been developed to compute seasonal index for time series data and it also seasonalise and desesaonalise the time series data.

r-survparamsim 0.1.7
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-survival@3.8-3 r-rlang@1.1.6 r-purrr@1.2.0 r-mvtnorm@1.3-3 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-ggplot2@4.0.1 r-forcats@1.0.1 r-eha@2.11.5 r-dplyr@1.1.4 r-broom@1.0.10
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/yoshidk6/survParamSim
Licenses: GPL 3
Build system: r
Synopsis: Parametric Survival Simulation with Parameter Uncertainty
Description:

Perform survival simulation with parametric survival model generated from survreg function in survival package. In each simulation coefficients are resampled from variance-covariance matrix of parameter estimates to capture uncertainty in model parameters. Prediction intervals of Kaplan-Meier estimates and hazard ratio of treatment effect can be further calculated using simulated survival data.

r-svsocket 1.1.5
Propagated dependencies: r-svmisc@1.4.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/SciViews/svSocket
Licenses: GPL 2
Build system: r
Synopsis: 'SciViews' - Socket Server
Description:

This package provides a socket server allows to connect clients to R.

r-sseparser 0.1.0
Propagated dependencies: r-stringr@1.6.0 r-rlang@1.1.6 r-r6@2.6.1 r-purrr@1.2.0 r-magrittr@2.0.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/calderonsamuel/SSEparser
Licenses: Expat
Build system: r
Synopsis: Parse Server-Sent Events
Description:

Functionality to parse server-sent events with a high-level interface that can be extended for custom applications.

r-svs 3.1.1
Propagated dependencies: r-matrix@1.7-4 r-gtools@3.9.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=svs
Licenses: GPL 3
Build system: r
Synopsis: Tools for Semantic Vector Spaces
Description:

Various tools for semantic vector spaces, such as correspondence analysis (simple, multiple and discriminant), latent semantic analysis, probabilistic latent semantic analysis, non-negative matrix factorization, latent class analysis, EM clustering, logratio analysis and log-multiplicative (association) analysis. Furthermore, there are specialized distance measures, plotting functions and some helper functions.

r-susier 0.14.2
Propagated dependencies: r-reshape@0.8.10 r-mixsqp@0.3-54 r-matrixstats@1.5.0 r-matrix@1.7-4 r-ggplot2@4.0.1 r-crayon@1.5.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/stephenslab/susieR
Licenses: Modified BSD
Build system: r
Synopsis: Sum of Single Effects Linear Regression
Description:

This package implements methods for variable selection in linear regression based on the "Sum of Single Effects" (SuSiE) model, as described in Wang et al (2020) <DOI:10.1101/501114> and Zou et al (2021) <DOI:10.1101/2021.11.03.467167>. These methods provide simple summaries, called "Credible Sets", for accurately quantifying uncertainty in which variables should be selected. The methods are motivated by genetic fine-mapping applications, and are particularly well-suited to settings where variables are highly correlated and detectable effects are sparse. The fitting algorithm, a Bayesian analogue of stepwise selection methods called "Iterative Bayesian Stepwise Selection" (IBSS), is simple and fast, allowing the SuSiE model be fit to large data sets (thousands of samples and hundreds of thousands of variables).

r-scirmdtheme 0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/oobianom/sciRmdTheme
Licenses: Expat
Build system: r
Synopsis: Upgraded 'Rmarkdown' Themes for Scientific Writing
Description:

This package provides a set of Rmarkdown themes for creating scientific and professional documents. Simple interface with features to ease navigation across the page and sub-pages.

r-spatstat-knet 3.1-2
Propagated dependencies: r-spatstat-utils@3.2-0 r-spatstat-univar@3.1-5 r-spatstat-sparse@3.1-0 r-spatstat-random@3.4-3 r-spatstat-model@3.5-0 r-spatstat-linnet@3.3-2 r-spatstat-geom@3.6-1 r-spatstat-explore@3.6-0 r-spatstat-data@3.1-9 r-spatstat@3.4-1 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=spatstat.Knet
Licenses: GPL 2+
Build system: r
Synopsis: Extension to 'spatstat' for Large Datasets on a Linear Network
Description:

Extension to the spatstat family of packages, for analysing large datasets of spatial points on a network. The geometrically- corrected K function is computed using a memory-efficient tree-based algorithm described by Rakshit, Baddeley and Nair (2019).

r-shinypayload 0.1.0
Propagated dependencies: r-shiny@1.11.1 r-jsonlite@2.0.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/PawanRamaMali/shinypayload
Licenses: Expat
Build system: r
Synopsis: Accept POST Data and URL Parameters in 'shiny' (Same-Port Integration)
Description:

Handle POST requests on a custom path (e.g., /ingress) inside the same shiny HTTP server using user interface functions and HTTP responses. Expose latest payload as a reactive and provide helpers for query parameters.

r-spiralize 1.1.0
Propagated dependencies: r-lubridate@1.9.4 r-globaloptions@0.1.2 r-getoptlong@1.0.5 r-complexheatmap@2.26.0 r-circlize@0.4.16
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/jokergoo/spiralize
Licenses: Expat
Build system: r
Synopsis: Visualize Data on Spirals
Description:

It visualizes data along an Archimedean spiral <https://en.wikipedia.org/wiki/Archimedean_spiral>, makes so-called spiral graph or spiral chart. It has two major advantages for visualization: 1. It is able to visualize data with very long axis with high resolution. 2. It is efficient for time series data to reveal periodic patterns.

r-sslfmm 0.1.0
Propagated dependencies: r-mvtnorm@1.3-3 r-matrixstats@1.5.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SSLfmm
Licenses: GPL 3
Build system: r
Synopsis: Semi-Supervised Learning under a Mixed-Missingness Mechanism in Finite Mixture Models
Description:

This package implements a semi-supervised learning framework for finite mixture models under a mixed-missingness mechanism. The approach models both missing completely at random (MCAR) and entropy-based missing at random (MAR) processes using a logisticâ entropy formulation. Estimation is carried out via an Expectationâ -Conditional Maximisation (ECM) algorithm with robust initialisation routines for stable convergence. The methodology relates to the statistical perspective and informative missingness behaviour discussed in Ahfock and McLachlan (2020) <doi:10.1007/s11222-020-09971-5> and Ahfock and McLachlan (2023) <doi:10.1016/j.ecosta.2022.03.007>. The package provides functions for data simulation, model estimation, prediction, and theoretical Bayes error evaluation for analysing partially labelled data under a mixed-missingness mechanism.

r-silp 1.0.3
Propagated dependencies: r-stringr@1.6.0 r-semtools@0.5-7 r-purrr@1.2.0 r-matrix@1.7-4 r-mass@7.3-65 r-lavaan@0.6-20
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/TomBJJJ/silp
Licenses: Expat
Build system: r
Synopsis: Conditional Process Analysis (CPA) via SEM Approach
Description:

Utilizes the Reliability-Adjusted Product Indicator (RAPI) method to estimate effects among latent variables, thus allowing for more precise definition and analysis of mediation and moderation models. Our simulation studies reveal that while silp may exhibit instability with smaller sample sizes and lower reliability scores (e.g., N = 100, omega = 0.7), implementing nearest positive definite matrix correction and bootstrap confidence interval estimation can significantly ameliorate this volatility. When these adjustments are applied, silp achieves estimations akin in quality to those derived from LMS. In conclusion, the silp package is a valuable tool for researchers seeking to explore complex relational structures between variables without resorting to commercial software. Cheung et al.(2021)<doi:10.1007/s10869-020-09717-0> Hsiao et al.(2018)<doi:10.1177/0013164416679877>.

r-subgrpid 0.13
Propagated dependencies: r-survival@3.8-3 r-rpart@4.1.24 r-matrix@1.7-4 r-mass@7.3-65 r-glmnet@4.1-10 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SubgrpID
Licenses: GPL 2+
Build system: r
Synopsis: Patient Subgroup Identification for Clinical Drug Development
Description:

Implementation of Sequential BATTing (bootstrapping and aggregating of thresholds from trees) for developing threshold-based multivariate (prognostic/predictive) biomarker signatures. Variable selection is automatically built-in. Final signatures are returned with interaction plots for predictive signatures. Cross-validation performance evaluation and testing dataset results are also output. Detail algorithms are described in Huang et al (2017) <doi:10.1002/sim.7236>.

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Total results: 69112