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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-surrogatetest 1.3
Propagated dependencies: r-survival@3.8-3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SurrogateTest
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Early Testing for a Treatment Effect using Surrogate Marker Information
Description:

This package provides functions to test for a treatment effect in terms of the difference in survival between a treatment group and a control group using surrogate marker information obtained at some early time point in a time-to-event outcome setting. Nonparametric kernel estimation is used to estimate the test statistic and perturbation resampling is used for variance estimation. More details will be available in the future in: Parast L, Cai T, Tian L (2019) ``Using a Surrogate Marker for Early Testing of a Treatment Effect" Biometrics, 75(4):1253-1263. <doi:10.1111/biom.13067>.

r-scholar 0.2.6
Propagated dependencies: r-xml2@1.5.0 r-tidygraph@1.3.1 r-stringr@1.6.0 r-rvest@1.0.5 r-rlang@1.1.6 r-r-cache@0.17.0 r-httr@1.4.7 r-ggraph@2.2.2 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/YuLab-SMU/scholar
Licenses: Expat
Build system: r
Synopsis: Analyse Citation Data from Google Scholar
Description:

This package provides functions to extract citation data from Google Scholar. Convenience functions are also provided for comparing multiple scholars and predicting future h-index values.

r-simsurvey 0.1.8
Propagated dependencies: r-stars@0.6-8 r-sf@1.0-23 r-rlang@1.1.6 r-progress@1.2.3 r-plotly@4.11.0 r-matrix@1.7-4 r-lifecycle@1.0.4 r-foreach@1.5.2 r-doparallel@1.0.17 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://paulregular.github.io/SimSurvey/
Licenses: GPL 3
Build system: r
Synopsis: Test Surveys by Simulating Spatially-Correlated Populations
Description:

Simulate age-structured populations that vary in space and time and explore the efficacy of a range of built-in or user-defined sampling protocols to reproduce the population parameters of the known population. (See Regular et al. (2020) <doi:10.1371/journal.pone.0232822> for more details).

r-sdprism2d 0.1.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SDPrism2D
Licenses: GPL 3
Build system: r
Synopsis: Visualizing the Standard Deviation as the Size of a Prism
Description:

We visualize the standard deviation of a data set as the size of a prism whose volume equals the total volume of several prisms made from the Empirical Cumulative Distribution Function.

r-sdear 1.0.2
Propagated dependencies: r-optisolve@1.0 r-dear@1.5.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SdeaR
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Stochastic Data Envelopment Analysis
Description:

Set of functions for Stochastic Data Envelopment Analysis. Chance constrained versions of radial, directional and additive DEA models are implemented, as long as super-efficiency models. See: Cooper, W.W.; Deng, H.; Huang, Z.; Li, S.X. (2002). <doi:10.1057/palgrave.jors.2601433>, Bolós, V.J.; Benà tez, R.; Coll-Serrano, V. (2024) <doi:10.1016/j.orp.2024.100307>.

r-strategy 1.0.1
Propagated dependencies: r-zoo@1.8-14 r-xts@0.14.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=Strategy
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Generic Framework to Analyze Trading Strategies
Description:

Users can build and test customized quantitative trading strategies. Some quantitative trading strategies are already implemented, e.g. various moving-average filters with trend following approaches. The implemented class called "Strategy" allows users to access several methods to analyze performance figures, plots and backtest the strategies. Furthermore, custom strategies can be added, a generic template is available. The custom strategies require a certain input and output so they can be called from the Strategy-constructor.

r-s4dm 0.0.1
Propagated dependencies: r-terra@1.8-86 r-sf@1.0-23 r-rvinecopulib@0.7.3.1.0 r-robust@0.7-5 r-rdpack@2.6.4 r-proc@1.19.0.1 r-np@0.60-18 r-mvtnorm@1.3-3 r-maxnet@0.1.4 r-kernlab@0.9-33 r-geometry@0.5.2 r-flexclust@1.5.0 r-dplyr@1.1.4 r-densratio@0.2.1 r-corpcor@1.6.10
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=S4DM
Licenses: Expat
Build system: r
Synopsis: Small Sample Size Species Distribution Modeling
Description:

This package implements a set of distribution modeling methods that are suited to species with small sample sizes (e.g., poorly sampled species or rare species). While these methods can also be used on well-sampled taxa, they are united by the fact that they can be utilized with relatively few data points. More details on the currently implemented methodologies can be found in Drake and Richards (2018) <doi:10.1002/ecs2.2373>, Drake (2015) <doi:10.1098/rsif.2015.0086>, and Drake (2014) <doi:10.1890/ES13-00202.1>.

r-stratifiedrf 0.2.2
Propagated dependencies: r-dplyr@1.1.4 r-c50@0.2.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=StratifiedRF
Licenses: GPL 3
Build system: r
Synopsis: Builds Trees by Sampling Variables in Groups
Description:

Random Forest-like tree ensemble that works with groups of predictor variables. When building a tree, a number of variables is taken randomly from each group separately, thus ensuring that it considers variables from each group for the splits. Useful when rows contain information about different things (e.g. user information and product information) and it's not sensible to make a prediction with information from only one group of variables, or when there are far more variables from one group than the other and it's desired to have groups appear evenly on trees. Trees are grown using the C5.0 algorithm rather than the usual CART algorithm. Supports parallelization (multithreaded), missing values in predictors, and categorical variables (without doing One-Hot encoding in the processing). Can also be used to create a regular (non-stratified) Random Forest-like model, but made up of C5.0 trees and with some additional control options. As it's built with C5.0 trees, it works only for classification (not for regression).

r-secr 5.4.2
Propagated dependencies: r-terra@1.8-86 r-stringr@1.6.0 r-sf@1.0-23 r-secrfunc@1.0.0 r-rcppparallel@5.1.11-1 r-rcpp@1.1.0 r-raster@3.6-32 r-nlme@3.1-168 r-mvtnorm@1.3-3 r-mgcv@1.9-4 r-mass@7.3-65 r-bh@1.87.0-1 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://www.otago.ac.nz/density/
Licenses: GPL 2+
Build system: r
Synopsis: Spatially Explicit Capture-Recapture
Description:

This package provides functions to estimate the density and size of a spatially distributed animal population sampled with an array of passive detectors, such as traps, or by searching polygons or transects. Models incorporating distance-dependent detection are fitted by maximizing the likelihood. Tools are included for data manipulation and model selection.

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-snpaimer 2.1.1
Propagated dependencies: r-yaml@2.3.10 r-withr@3.0.2 r-tidyr@1.3.1 r-readr@2.1.6 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-foreach@1.5.2 r-forcats@1.0.1 r-dplyr@1.1.4 r-doparallel@1.0.17 r-adegenet@2.1.11
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/OksanaVe/snpAIMeR
Licenses: Expat
Build system: r
Synopsis: Assess the Diagnostic Power of Genomic Marker Combinations
Description:

Population genetics package for designing diagnostic panels. Candidate markers, marker combinations, and different panel sizes are assessed for how well they can predict the source population of known samples. Requires a genotype file of candidate markers in STRUCTURE format. Methods for population cross-validation are described in Jombart (2008) <doi:10.1093/bioinformatics/btn129>.

r-solvesaphe 2.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://CRAN.R-project.org/package=SolveSAPHE
Licenses: GPL 2+
Build system: r
Synopsis: Solver Suite for Alkalinity-PH Equations
Description:

Universal and robust algorithm for solving the total alkalinity-pH equation presented in G. Munhoven (2013) <doi:10.5194/gmd-6-1367-2013> and G. Munhoven (2021) <doi:10.5194/gmd-2020-447>. The total alkalinity-pH equation relates total alkalinity and pH for a given set of acid-base concentrations in a given water sample, among which carbonic acid. This package is particularly useful in marine chemistry involving dissolved inorganic carbon. Original package in Fortran can be found at <doi:10.5281/zenodo.4328965>.

r-sharpr2 1.1.1.0
Propagated dependencies: r-mvtnorm@1.3-3 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=sharpr2
Licenses: GPL 2+
Build system: r
Synopsis: Estimating Regulatory Scores and Identifying ATAC-STARR Data
Description:

An algorithm for identifying high-resolution driver elements for datasets from a high-definition reporter assay library. Xinchen Wang, Liang He, Sarah Goggin, Alham Saadat, Li Wang, Melina Claussnitzer, Manolis Kellis (2017) <doi:10.1101/193136>.

r-simbiid 0.2.2
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-rcppxptrutils@0.1.3 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-rcolorbrewer@1.1-3 r-purrr@1.2.0 r-mvtnorm@1.3-3 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/tjmckinley/SimBIID
Licenses: GPL 3+
Build system: r
Synopsis: Simulation-Based Inference Methods for Infectious Disease Models
Description:

This package provides some code to run simulations of state-space models, and then use these in the Approximate Bayesian Computation Sequential Monte Carlo (ABC-SMC) algorithm of Toni et al. (2009) <doi:10.1098/rsif.2008.0172> and a bootstrap particle filter based particle Markov chain Monte Carlo (PMCMC) algorithm (Andrieu et al., 2010 <doi:10.1111/j.1467-9868.2009.00736.x>). Also provides functions to plot and summarise the outputs.

r-simcomp 3.6
Propagated dependencies: r-mvtnorm@1.3-3 r-multcomp@1.4-29 r-mratios@1.4.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SimComp
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Simultaneous Comparisons for Multiple Endpoints
Description:

Simultaneous tests and confidence intervals are provided for one-way experimental designs with one or many normally distributed, primary response variables (endpoints). Differences (Hasler and Hothorn, 2011 <doi:10.2202/1557-4679.1258>) or ratios (Hasler and Hothorn, 2012 <doi:10.1080/19466315.2011.633868>) of means can be considered. Various contrasts can be chosen, unbalanced sample sizes are allowed as well as heterogeneous variances (Hasler and Hothorn, 2008 <doi:10.1002/bimj.200710466>) or covariance matrices (Hasler, 2014 <doi:10.1515/ijb-2012-0015>).

r-steepness 0.3-0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=steepness
Licenses: GPL 2+
Build system: r
Synopsis: Testing Steepness of Dominance Hierarchies
Description:

The steepness package computes steepness as a property of dominance hierarchies. Steepness is defined as the absolute slope of the straight line fitted to the normalized David's scores. The normalized David's scores can be obtained on the basis of dyadic dominance indices corrected for chance or by means of proportions of wins. Given an observed sociomatrix, it computes hierarchy's steepness and estimates statistical significance by means of a randomization test.

r-svalignr 0.9.2
Propagated dependencies: r-stringr@1.6.0 r-polychrome@1.5.4 r-oompabase@3.2.10 r-nameneedle@1.2.8 r-igraph@2.2.1 r-dendextend@1.19.1 r-colorspace@2.1-2 r-biostrings@2.78.0 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: http://oompa.r-forge.r-project.org/
Licenses: ASL 2.0
Build system: r
Synopsis: Recovering Structure of Long Molecules from Structural Variation Data
Description:

This package implements a method to combine multiple levels of multiple sequence alignment to uncover the structure of complex DNA rearrangements.

r-starling 0.6.5
Propagated dependencies: r-tidyr@1.3.1 r-stringr@1.6.0 r-rlang@1.1.6 r-reclin2@0.6.0 r-magrittr@2.0.4 r-lubridate@1.9.4 r-janitor@2.2.1 r-dplyr@1.1.4 r-digest@0.6.39 r-datawizard@1.3.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=starling
Licenses: GPL 3+
Build system: r
Synopsis: Link Infectious Disease Cases to Vaccination and Hospitalization Records
Description:

Facilitates probabilistic record linkage between infectious disease surveillance datasets (notifiable disease registers, outbreak line-lists), vaccination registries, and hospitalization records using methods based on Fellegi and Sunter (1969) <doi:10.1080/01621459.1969.10501049> and Sayers et al. (2016) <doi:10.1093/ije/dyv322>. The package provides core functions for data preparation, linkage, and analysis: clean_the_nest() standardizes variable names and formats across heterogeneous datasets; murmuration() performs machine learning-based record linkage using blocking variables and similarity metrics; molting() deidentifies datasets for secure sharing; homing() re-identifies previously deidentified datasets; plumage() identifies and categorizes comorbidities; and preening() creates analysis-ready variables including age categories and temporal groupings. Designed for epidemiological research linking acute and post-acute disease outcomes to vaccination status and healthcare utilization. Supports multiple linkage scenarios including case-to-vaccination, case-to-hospitalization, and event-based vaccination status determination (e.g., outbreak attendees, flight passengers, exposure site visitors).

r-sonar 1.0.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sonar
Licenses: GPL 3+
Build system: r
Synopsis: Fundamental Formulas for Sonar
Description:

Formulas for calculating sound velocity, water pressure, depth, density, absorption and sonar equations.

r-survdisc 0.1.1
Propagated dependencies: r-survival@3.8-3 r-simex@1.8 r-nlme@3.1-168 r-mvtnorm@1.3-3 r-mass@7.3-65 r-cubature@2.1.4-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SurvDisc
Licenses: GPL 2
Build system: r
Synopsis: Discrete Time Survival and Longitudinal Data Analysis
Description:

Various functions for discrete time survival analysis and longitudinal analysis. SIMEX method for correcting for bias for errors-in-variables in a mixed effects model. Asymptotic mean and variance of different proportional hazards test statistics using different ties methods given two survival curves and censoring distributions. Score test and Wald test for regression analysis of grouped survival data. Calculation of survival curves for events defined by the response variable in a mixed effects model crossing a threshold with or without confirmation.

r-svmd 0.1.0
Propagated dependencies: r-vmdecomp@1.0.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SVMD
Licenses: GPL 3
Build system: r
Synopsis: Spearman Variational Mode Decomposition
Description:

In practice, it is difficult to determine the number of decomposition modes, K, for Variational Mode Decomposition (VMD). To overcome this issue, this study offers Spearman Variational Mode Decomposition (SVMD), a method that uses the Spearman correlation coefficient to calculate the ideal mode number. Unlike the Pearson correlation coefficient, which only returns a perfect value when X and Y are linearly connected, the Spearman correlation can be calculated without knowing the probability distributions of X and Y. The Spearman correlation coefficient, also called Spearman's rank correlation coefficient, is a subset of a wider correlation coefficient. As VMD decomposes a signal, the Spearman correlation coefficient between the reconstructed and original sequences rises as the mode number K increases. Once the signal has been fully decomposed, subsequent increases in K cause the correlation to gradually level off. When the correlation reaches a specific level, VMD is said to have adequately decomposed the signal. Numerous experiments revealed that a threshold of 0.997 produces the best denoising effect, so the threshold is set at 0.997. This package has been developed using concept of Yang et al. (2021)<doi:10.1016/j.aej.2021.01.055>.

r-sqlscore 0.1.4
Propagated dependencies: r-dbplyr@2.5.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/wwbrannon/sqlscore/
Licenses: Expat
Build system: r
Synopsis: Utilities for Generating SQL Queries from Model Objects
Description:

This package provides utilities for generating SQL queries (particularly CREATE TABLE statements) from R model objects. The most important use case is generating SQL to score a generalized linear model or related model represented as an R object, in which case the package handles parsing formula operators and including the model's response function.

r-simplegraphdb 2021.03.10
Propagated dependencies: r-rsqlite@2.4.4 r-rjson@0.2.23 r-dbi@1.2.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/mikeasilva/simplegraphdb
Licenses: Expat
Build system: r
Synopsis: Simple Graph Database
Description:

This is a graph database in SQLite'. It is inspired by Denis Papathanasiou's Python simple-graph project on GitHub'.

r-sgt 2.0
Propagated dependencies: r-optimx@2025-4.9 r-numderiv@2016.8-1.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sgt
Licenses: GPL 3+
Build system: r
Synopsis: Skewed Generalized T Distribution Tree
Description:

Density, distribution function, quantile function and random generation for the skewed generalized t distribution. This package also provides a function that can fit data to the skewed generalized t distribution using maximum likelihood estimation.

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