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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-summarytabl 0.2.1
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-rlang@1.1.6 r-purrr@1.2.0 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://anyamemensah.github.io/summarytabl/
Licenses: Expat
Build system: r
Synopsis: Generate Summary Tables for Categorical, Ordinal, and Continuous Data
Description:

This package provides functions for tabulating and summarizing categorical, multiple response, ordinal, and continuous variables in R data frames. Makes it easy to create clear, structured summary tables, so you spend less time wrangling data and more time interpreting it.

r-semboottools 0.1.1
Propagated dependencies: r-psych@2.5.6 r-lavaan-printer@0.1.0 r-lavaan@0.6-20 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://Yangzhen1999.github.io/semboottools/
Licenses: GPL 3+
Build system: r
Synopsis: Bootstrapping Helpers for Structural Equation Modelling
Description:

This package provides a collection of helper functions for forming bootstrapping confidence intervals and examining bootstrap estimates in structural equation modelling. Currently supports models fitted by the lavaan package by Rosseel (2012) <doi: 10.18637/jss.v048.i02>.

r-sdmtmb 1.0.0
Propagated dependencies: r-tmb@1.9.18 r-rlang@1.1.6 r-reformulas@0.4.2 r-rcppeigen@0.3.4.0.2 r-nlme@3.1-168 r-mvtnorm@1.3-3 r-mgcv@1.9-4 r-matrix@1.7-4 r-lifecycle@1.0.4 r-generics@0.1.4 r-fmesher@0.5.0 r-fishmod@0.29.2 r-cli@3.6.5 r-assertthat@0.2.1 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://sdmTMB.github.io/sdmTMB/
Licenses: GPL 3
Build system: r
Synopsis: Spatial and Spatiotemporal SPDE-Based GLMMs with 'TMB'
Description:

This package implements spatial and spatiotemporal GLMMs (Generalized Linear Mixed Effect Models) using TMB', fmesher', and the SPDE (Stochastic Partial Differential Equation) Gaussian Markov random field approximation to Gaussian random fields. One common application is for spatially explicit species distribution models (SDMs). See Anderson et al. (2025) <doi:10.18637/jss.v115.i02>.

r-stilt 1.3.1
Propagated dependencies: 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=stilt
Licenses: GPL 3
Build system: r
Synopsis: Separable Gaussian Process Interpolation (Emulation)
Description:

This package provides functions for simplified emulation of time series computer model output in model parameter space using Gaussian processes. Stilt can be used more generally for Kriging of spatio-temporal fields. There are functions to predict at new parameter settings, to test the emulator using cross-validation (which includes information on 95% confidence interval empirical coverage), and to produce contour plots over 2D slices in model parameter space.

r-snowflakes 1.0.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=snowflakes
Licenses: GPL 2+
Build system: r
Synopsis: Random Snowflake Generator
Description:

The function generates and plots random snowflakes. Each snowflake is defined by a given diameter, width of the crystal, color, and random seed. Snowflakes are plotted in such way that they always remain round, no matter what the aspect ratio of the plot is. Snowflakes can be created using transparent colors, which creates a more interesting, somewhat realistic, image. Images of the snowflakes can be separately saved as svg files and used in websites as static or animated images.

r-synergylmm 1.1.2
Propagated dependencies: r-rlang@1.1.6 r-performance@0.15.2 r-nlmeu@0.71.7 r-nlme@3.1-168 r-mass@7.3-65 r-marginaleffects@0.31.0 r-magrittr@2.0.4 r-lattice@0.22-7 r-ggplot2@4.0.1 r-fbasics@4041.97 r-dplyr@1.1.4 r-cowplot@1.2.0 r-clubsandwich@0.6.1 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/RafRomB/SynergyLMM
Licenses: GPL 3+
Build system: r
Synopsis: Statistical Framework for in Vivo Drug Combination Studies
Description:

This package provides a framework for evaluating drug combination effects in preclinical in vivo studies. SynergyLMM provides functions to analyze longitudinal tumor growth experiments using mixed-effects models, perform time-resolved analyses of synergy and antagonism, evaluate model diagnostics and performance, and assess both post-hoc and a priori statistical power. The calculation of drug combination synergy follows the statistical framework provided by Demidenko and Miller (2019, <doi:10.1371/journal.pone.0224137>). The implementation and analysis of linear mixed-effect models is based on the methods described by Pinheiro and Bates (2000, <doi:10.1007/b98882>), and GaÅ ecki and Burzykowski (2013, <doi:10.1007/978-1-4614-3900-4>).

r-shidashi 0.1.6
Propagated dependencies: r-yaml@2.3.10 r-shiny@1.11.1 r-jsonlite@2.0.0 r-httr@1.4.7 r-formatr@1.14 r-fastmap@1.2.0 r-digest@0.6.39
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://dipterix.org/shidashi/
Licenses: Expat
Build system: r
Synopsis: Shiny Dashboard Template System
Description:

This package provides a template system based on AdminLTE3 (<https://adminlte.io/themes/v3/>) theme. Comes with default theme that can be easily customized. Developers can upload modified templates on Github', and users can easily download templates with RStudio project wizard. The key features of the default template include light and dark theme switcher, resizing graphs, synchronizing inputs across sessions, new notification system, fancy progress bars, and card-like flip panels with back sides, as well as various of HTML tool widgets.

r-sts 1.4
Propagated dependencies: r-tm@0.7-16 r-stm@1.3.8 r-slam@0.1-55 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mvtnorm@1.3-3 r-matrixstats@1.5.0 r-matrix@1.7-4 r-glmnet@4.1-10 r-ggplot2@4.0.1 r-foreach@1.5.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sts
Licenses: Expat
Build system: r
Synopsis: Estimation of the Structural Topic and Sentiment-Discourse Model for Text Analysis
Description:

The Structural Topic and Sentiment-Discourse (STS) model allows researchers to estimate topic models with document-level metadata that determines both topic prevalence and sentiment-discourse. The sentiment-discourse is modeled as a document-level latent variable for each topic that modulates the word frequency within a topic. These latent topic sentiment-discourse variables are controlled by the document-level metadata. The STS model can be useful for regression analysis with text data in addition to topic modelingâ s traditional use of descriptive analysis. The method was developed in Chen and Mankad (2024) <doi:10.1287/mnsc.2022.00261>.

r-simex 1.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: http://wolfganglederer.github.io/simex/
Licenses: GPL 3
Build system: r
Synopsis: SIMEX- And MCSIMEX-Algorithm for Measurement Error Models
Description:

Implementation of the SIMEX-Algorithm by Cook & Stefanski (1994) <doi:10.1080/01621459.1994.10476871> and MCSIMEX by Küchenhoff, Mwalili & Lesaffre (2006) <doi:10.1111/j.1541-0420.2005.00396.x>.

r-shinysbm 0.2.0
Propagated dependencies: r-visnetwork@2.1.4 r-stringr@1.6.0 r-shinydashboard@0.7.3 r-shinyalert@3.1.0 r-shiny@1.11.1 r-sbm@0.4.7 r-rmarkdown@2.30 r-purrr@1.2.0 r-patchwork@1.3.2 r-magrittr@2.0.4 r-golem@0.5.1 r-ggplot2@4.0.1 r-fresh@0.2.2 r-flextable@0.9.10 r-dt@0.34.0 r-dplyr@1.1.4 r-data-table@1.17.8 r-config@0.3.2 r-colourpicker@1.3.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://shinysbm-theodore-vanrenterghem-b12616c23cfbfb3f0fe520178bcb95a.pages-forge.inrae.fr/
Licenses: Expat
Build system: r
Synopsis: 'shiny' Application to Use the Stochastic Block Model
Description:

This package provides a shiny interface for a simpler use of the sbm R package. It also contains useful functions to easily explore the sbm package results. With this package you should be able to use the stochastic block model without any knowledge in R, get automatic reports and nice visuals, as well as learning the basic functions of sbm'.

r-supernova 3.0.1
Propagated dependencies: r-vctrs@0.6.5 r-tibble@3.3.0 r-stringr@1.6.0 r-rlang@1.1.6 r-purrr@1.2.0 r-pillar@1.11.1 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/UCLATALL/supernova
Licenses: GPL 3+
Build system: r
Synopsis: Judd, McClelland, & Ryan Formatting for ANOVA Output
Description:

This package produces ANOVA tables in the format used by Judd, McClelland, and Ryan (2017, ISBN: 978-1138819832) in their introductory textbook, Data Analysis. This includes proportional reduction in error and formatting to improve ease the transition between the book and R.

r-shinydrive 0.1.5
Propagated dependencies: r-zip@2.3.3 r-yaml@2.3.10 r-shiny@1.11.1 r-r-utils@2.13.0 r-knitr@1.50 r-htmltools@0.5.8.1 r-dt@0.34.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=shinydrive
Licenses: GPL 3
Build system: r
Synopsis: File Sharing Shiny Module
Description:

Shiny module for easily sharing files between users. Admin can add, remove, edit and download file. User can only download file. It's also possible to manage files using R functions directly.

r-seqimpute 2.2.1
Propagated dependencies: r-traminerextras@0.6.8 r-traminer@2.2-13 r-stringr@1.6.0 r-rms@8.1-0 r-ranger@0.17.0 r-plyr@1.8.9 r-parallelly@1.45.1 r-nnet@7.3-20 r-mlr@2.19.3 r-mice@3.18.0 r-foreach@1.5.2 r-dplyr@1.1.4 r-dosnow@1.0.20 r-dorng@1.8.6.2 r-dfidx@0.2-0 r-cluster@2.1.8.1 r-amelia@1.8.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/emerykevin/seqimpute
Licenses: GPL 2
Build system: r
Synopsis: Imputation of Missing Data in Sequence Analysis
Description:

Multiple imputation of missing data in a dataset using MICT or MICT-timing methods. The core idea of the algorithms is to fill gaps of missing data, which is the typical form of missing data in a longitudinal setting, recursively from their edges. Prediction is based on either a multinomial or random forest regression model. Covariates and time-dependent covariates can be included in the model.

r-spcadjust 1.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=spcadjust
Licenses: GPL 2+
Build system: r
Synopsis: Functions for Calibrating Control Charts
Description:

Calibration of thresholds of control charts such as CUSUM charts based on past data, taking estimation error into account.

r-siren 1.0.6
Propagated dependencies: r-psych@2.5.6 r-lavaan@0.6-20 r-efa-mrfa@1.1.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=siren
Licenses: GPL 3
Build system: r
Synopsis: Hybrid FA-CFA for Controlling Acquiescence in Restricted Factorial Solutions
Description:

This package performs hybrid multi-stage factor analytic procedure for controlling acquiescence in restricted solutions (Ferrando & Lorenzo-Seva, 2000 <https://www.uv.es/revispsi/articulos3.00/ferran7.pdf>).

r-scoutbar 0.2.5
Propagated dependencies: r-shiny@1.11.1 r-reactr@0.6.1 r-htmltools@0.5.8.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=scoutbaR
Licenses: Expat
Build system: r
Synopsis: Spotlight 'React' Widget for 'shiny' Apps
Description:

This package creates a contextual menu that can be triggered with keyboard shortcuts or programmatically. This can replace traditional sidebars or navigation bars, thereby enhancing the user experience with lighter user interfaces.

r-stray 0.1.1
Propagated dependencies: r-pcapp@2.0-5 r-ks@1.15.1 r-ggplot2@4.0.1 r-fnn@1.1.4.1 r-colorspace@2.1-2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=stray
Licenses: GPL 2
Build system: r
Synopsis: Anomaly Detection in High Dimensional and Temporal Data
Description:

This is a modification of HDoutliers package. The HDoutliers algorithm is a powerful unsupervised algorithm for detecting anomalies in high-dimensional data, with a strong theoretical foundation. However, it suffers from some limitations that significantly hinder its performance level, under certain circumstances. This package implements the algorithm proposed in Talagala, Hyndman and Smith-Miles (2019) <arXiv:1908.04000> for detecting anomalies in high-dimensional data that addresses these limitations of HDoutliers algorithm. We define an anomaly as an observation that deviates markedly from the majority with a large distance gap. An approach based on extreme value theory is used for the anomalous threshold calculation.

r-syrup 0.1.4
Propagated dependencies: r-withr@3.0.2 r-vctrs@0.6.5 r-tibble@3.3.0 r-rlang@1.1.6 r-purrr@1.2.0 r-ps@1.9.1 r-dplyr@1.1.4 r-callr@3.7.6 r-bench@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/simonpcouch/syrup
Licenses: Expat
Build system: r
Synopsis: Measure Memory and CPU Usage for Parallel R Code
Description:

Measures memory and CPU usage of R code by regularly taking snapshots of calls to the system command ps'. The package provides an entry point (albeit coarse) to profile usage of system resources by R code run in parallel.

r-shapr 1.0.8
Propagated dependencies: r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-matrix@1.7-4 r-future-apply@1.20.0 r-data-table@1.17.8 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://norskregnesentral.github.io/shapr/
Licenses: Expat
Build system: r
Synopsis: Prediction Explanation with Dependence-Aware Shapley Values
Description:

Complex machine learning models are often hard to interpret. However, in many situations it is crucial to understand and explain why a model made a specific prediction. Shapley values is the only method for such prediction explanation framework with a solid theoretical foundation. Previously known methods for estimating the Shapley values do, however, assume feature independence. This package implements methods which accounts for any feature dependence, and thereby produces more accurate estimates of the true Shapley values. An accompanying Python wrapper ('shaprpy') is available through PyPI.

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-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.

r-ssmrob 1.0
Propagated dependencies: r-sampleselection@1.2-14 r-robustbase@0.99-6 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=ssmrob
Licenses: GPL 2
Build system: r
Synopsis: Robust Estimation and Inference in Sample Selection Models
Description:

Package provides a set of tools for robust estimation and inference for models with sample selectivity and endogenous treatment model. For details, see Zhelonkin and Ronchetti (2021) <doi:10.18637/jss.v099.i04>.

r-starts 1.3-8
Propagated dependencies: r-sirt@4.2-133 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-lam@0.7-22 r-cdm@8.3-14
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/alexanderrobitzsch/STARTS
Licenses: GPL 2+
Build system: r
Synopsis: Functions for the STARTS Model
Description:

This package contains functions for estimating the STARTS model of Kenny and Zautra (1995, 2001) <DOI:10.1037/0022-006X.63.1.52>, <DOI:10.1037/10409-008>. Penalized maximum likelihood estimation and Markov Chain Monte Carlo estimation are also provided, see Luedtke, Robitzsch and Wagner (2018) <DOI:10.1037/met0000155>.

r-spedecon 0.1
Propagated dependencies: r-quadprog@1.5-8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://www.davidjkent.org
Licenses: GPL 3
Build system: r
Synopsis: Smoothness-Penalized Deconvolution for Density Estimation Under Measurement Error
Description:

This package implements the Smoothness-Penalized Deconvolution method for estimating a probability density under measurement error of Kent and Ruppert (2023) <doi:10.1080/01621459.2023.2259028>. The estimator is formed by computing a histogram of the error-contaminated data, and then finding an estimate that minimizes a reconstruction error plus a smoothness-inducing penalty term. The primary function, sped(), takes the data and error distribution, and returns the estimator as a function.

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