_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/

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-sfcurve 1.0.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/jokergoo/sfcurve
Licenses: Expat
Build system: r
Synopsis: 2x2, 3x3 and Nxn Space-Filling Curves
Description:

Implementation of all possible forms of 2x2 and 3x3 space-filling curves, i.e., the generalized forms of the Hilbert curve <https://en.wikipedia.org/wiki/Hilbert_curve>, the Peano curve <https://en.wikipedia.org/wiki/Peano_curve> and the Peano curve in the meander type (Figure 5 in <https://eudml.org/doc/141086>). It can generates nxn curves expanded from any specific level-1 units. It also implements the H-curve and the three-dimensional Hilbert curve.

r-sensitivity2x2xk 1.01
Propagated dependencies: r-mvtnorm@1.3-3 r-biasedurn@2.0.12
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sensitivity2x2xk
Licenses: GPL 2
Build system: r
Synopsis: Sensitivity Analysis for 2x2xk Tables in Observational Studies
Description:

This package performs exact or approximate adaptive or nonadaptive Cochran-Mantel-Haenszel-Birch tests and sensitivity analyses for one or two 2x2xk tables in observational studies.

r-scriptexec 0.3.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/sagiegurari/scriptexec
Licenses: ASL 2.0
Build system: r
Synopsis: Execute Native Scripts
Description:

Run complex native scripts with a single command, similar to system commands.

r-sde 2.0.21
Propagated dependencies: r-zoo@1.8-14 r-mass@7.3-65 r-fda@6.3.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sde
Licenses: GPL 2+
Build system: r
Synopsis: Simulation and Inference for Stochastic Differential Equations
Description:

Description: Provides functions for simulation and inference for stochastic differential equations (SDEs). It accompanies the book "Simulation and Inference for Stochastic Differential Equations: With R Examples" (Iacus, 2008, Springer; ISBN: 978-0-387-75838-1).

r-sbmsdp 0.2
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sbmSDP
Licenses: GPL 3
Build system: r
Synopsis: Semidefinite Programming for Fitting Block Models of Equal Block Sizes
Description:

An ADMM implementation of SDP-1, a semidefinite programming relaxation of the maximum likelihood estimator for fitting a block model. SDP-1 has a tendency to produce equal-sized blocks and is ideal for producing a form of network histogram approximating a nonparametric graphon model. Alternatively, it can be used for community detection. (This is experimental code, proceed with caution.).

r-scdtb 0.2.0
Propagated dependencies: r-sn@2.1.1 r-shinythemes@1.2.0 r-shiny@1.11.1 r-nlme@3.1-168 r-mmints@0.2.0 r-mmcards@0.1.1 r-mass@7.3-65 r-ggplot2@4.0.1 r-dt@0.34.0 r-broom-mixed@0.2.9.7
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/mightymetrika/scdtb
Licenses: Expat
Build system: r
Synopsis: Single Case Design Tools
Description:

In some situations where researchers would like to demonstrate causal effects, it is hard to obtain a sample size that would allow for a well-powered randomized controlled trial. Single case designs are experimental designs that can be used to demonstrate causal effects with only one participant or with only a few participants. The scdtb package provides a suite of tools for analyzing data from studies that use single case designs. The nap() function can be used to compute the nonoverlap of all pairs as outlined by the What Works Clearinghouse (2022) <https://ies.ed.gov/ncee/wwc/Handbooks>. The package also offers the mixed_model_analysis() and cross_lagged() functions which implement mixed effects models and cross lagged analyses as described in Maric & van der Werff (2020) <doi:10.4324/9780429273872-9>. The randomization_test() function implements randomization tests based on methods presented in Onghena (2020) <doi:10.4324/9780429273872-8>. The scdtb() shiny application can be used to upload single case design data and access various scdtb tools for plotting and analysis.

r-survpen 2.0.2
Propagated dependencies: r-statmod@1.5.1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/fauvernierma/survPen
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Multidimensional Penalized Splines for (Excess) Hazard Models, Relative Mortality Ratio Models and Marginal Intensity Models
Description:

Fits (excess) hazard, relative mortality ratio or marginal intensity models with multidimensional penalized splines allowing for time-dependent effects, non-linear effects and interactions between several continuous covariates. In survival and net survival analysis, in addition to modelling the effect of time (via the baseline hazard), one has often to deal with several continuous covariates and model their functional forms, their time-dependent effects, and their interactions. Model specification becomes therefore a complex problem and penalized regression splines represent an appealing solution to that problem as splines offer the required flexibility while penalization limits overfitting issues. Current implementations of penalized survival models can be slow or unstable and sometimes lack some key features like taking into account expected mortality to provide net survival and excess hazard estimates. In contrast, survPen provides an automated, fast, and stable implementation (thanks to explicit calculation of the derivatives of the likelihood) and offers a unified framework for multidimensional penalized hazard and excess hazard models. Later versions (>2.0.0) include penalized models for relative mortality ratio, and marginal intensity in recurrent event setting. survPen may be of interest to those who 1) analyse any kind of time-to-event data: mortality, disease relapse, machinery breakdown, unemployment, etc 2) wish to describe the associated hazard and to understand which predictors impact its dynamics, 3) wish to model the relative mortality ratio between a cohort and a reference population, 4) wish to describe the marginal intensity for recurrent event data. See Fauvernier et al. (2019a) <doi:10.21105/joss.01434> for an overview of the package and Fauvernier et al. (2019b) <doi:10.1111/rssc.12368> for the method.

r-scatterd3 1.0.1
Propagated dependencies: r-htmlwidgets@1.6.4 r-ellipse@0.5.0 r-digest@0.6.39
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://juba.github.io/scatterD3/
Licenses: GPL 3+
Build system: r
Synopsis: D3 JavaScript Scatterplot from R
Description:

This package creates D3 JavaScript scatterplots from R with interactive features : panning, zooming, tooltips, etc.

r-survtrunc 0.2.0
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=SurvTrunc
Licenses: GPL 2
Build system: r
Synopsis: Analysis of Doubly Truncated Data
Description:

Package performs Cox regression and survival distribution function estimation when the survival times are subject to double truncation. In case that the survival and truncation times are quasi-independent, the estimation procedure for each method involves inverse probability weighting, where the weights correspond to the inverse of the selection probabilities and are estimated using the survival times and truncation times only. A test for checking this independence assumption is also included in this package. The functions available in this package for Cox regression, survival distribution function estimation, and testing independence under double truncation are based on the following methods, respectively: Rennert and Xie (2018) <doi:10.1111/biom.12809>, Shen (2010) <doi:10.1007/s10463-008-0192-2>, Martin and Betensky (2005) <doi:10.1198/016214504000001538>. When the survival times are dependent on at least one of the truncation times, an EM algorithm is employed to obtain point estimates for the regression coefficients. The standard errors are calculated using the bootstrap method. See Rennert and Xie (2022) <doi:10.1111/biom.13451>. Both the independent and dependent cases assume no censoring is present in the data. Please contact Lior Rennert <liorr@clemson.edu> for questions regarding function coxDT and Yidan Shi <yidan.shi@pennmedicine.upenn.edu> for questions regarding function coxDTdep.

r-ssw 0.2.1
Dependencies: python@3.11.14
Propagated dependencies: r-reticulate@1.44.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://nanx.me/ssw-r/
Licenses: Expat
Build system: r
Synopsis: Striped Smith-Waterman Algorithm for Sequence Alignment using SIMD
Description:

This package provides an R interface for SSW (Striped Smith-Waterman) via its Python binding ssw-py'. SSW is a fast C and C++ implementation of the Smith-Waterman algorithm for pairwise sequence alignment using Single-Instruction-Multiple-Data (SIMD) instructions. SSW enhances the standard algorithm by efficiently returning alignment information and suboptimal alignment scores. The core SSW library offers performance improvements for various bioinformatics tasks, including protein database searches, short-read alignments, primary and split-read mapping, structural variant detection, and read-overlap graph generation. These features make SSW particularly useful for genomic applications. Zhao et al. (2013) <doi:10.1371/journal.pone.0082138> developed the original C and C++ implementation.

r-synth 1.1-9
Propagated dependencies: r-rgenoud@5.9-0.11 r-optimx@2025-4.9 r-kernlab@0.9-33
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://web.stanford.edu/~jhain/
Licenses: GPL 2+
Build system: r
Synopsis: Synthetic Control Group Method for Comparative Case Studies
Description:

This package implements the synthetic control group method for comparative case studies as described in Abadie and Gardeazabal (2003) and Abadie, Diamond, and Hainmueller (2010, 2011, 2014). The synthetic control method allows for effect estimation in settings where a single unit (a state, country, firm, etc.) is exposed to an event or intervention. It provides a data-driven procedure to construct synthetic control units based on a weighted combination of comparison units that approximates the characteristics of the unit that is exposed to the intervention. A combination of comparison units often provides a better comparison for the unit exposed to the intervention than any comparison unit alone.

r-simplecolors 0.1.4
Propagated dependencies: r-stringr@1.6.0 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-forcats@1.0.1 r-dplyr@1.1.4 r-colorspace@2.1-2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/rjake/simplecolors
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Access Color Names Using a Standardized Nomenclature
Description:

This package provides a curated set of colors that are called using a standardized syntax: saturation + hue + lightness. For example, "brightblue4" and "mutedred2". Functions exists to return individual colors by name or to build palettes across or within hues. Most functions allow you to visualize the palettes in addition to returning the desired hex codes.

r-sglg 0.2.6
Propagated dependencies: r-teachingsampling@4.1.1 r-survival@3.8-3 r-rcpp@1.1.0 r-progress@1.2.3 r-pracma@2.4.6 r-plotly@4.11.0 r-plot3d@1.4.2 r-moments@0.14.1 r-magrittr@2.0.4 r-gridextra@2.3 r-ggplot2@4.0.1 r-formula@1.2-5 r-adequacymodel@2.0.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sglg
Licenses: GPL 3
Build system: r
Synopsis: Fitting Semi-Parametric Generalized log-Gamma Regression Models
Description:

Set of tools to fit a linear multiple or semi-parametric regression models with the possibility of non-informative random right or left censoring. Under this setup, the localization parameter of the response variable distribution is modeled by using linear multiple regression or semi-parametric functions, whose non-parametric components may be approximated by natural cubic spline or P-splines. The supported distribution for the model error is a generalized log-gamma distribution which includes the generalized extreme value and standard normal distributions as important special cases. Inference is based on likelihood, penalized likelihood and bootstrap methods. Lastly, some numerical and graphical devices for diagnostic of the fitted models are offered.

r-survimpute 0.1.0
Propagated dependencies: r-vgam@1.1-13 r-survival@3.8-3 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=SurvImpute
Licenses: GPL 3
Build system: r
Synopsis: Multiple Imputation for Missing Covariates in Time-to-Event Data
Description:

Generates multiple imputed datasets from a substantive model compatible fully conditional specification model for time-to-event data. Our method assumes that the censoring process also depends on the covariates with missing values. Details will be available in an upcoming publication.

r-sparrafairness 0.1.0.0
Propagated dependencies: r-scales@1.4.0 r-ranger@0.17.0 r-patchwork@1.3.2 r-mvtnorm@1.3-3 r-matrixstats@1.5.0 r-ggrepel@0.9.6 r-ggplot2@4.0.1 r-cvauc@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SPARRAfairness
Licenses: GPL 3+
Build system: r
Synopsis: Analysis of Differential Behaviour of SPARRA Score Across Demographic Groups
Description:

The SPARRA risk score (Scottish Patients At Risk of admission and Re-Admission) estimates yearly risk of emergency hospital admission using electronic health records on a monthly basis for most of the Scottish population. This package implements a suite of functions used to analyse the behaviour and performance of the score, focusing particularly on differential performance over demographically-defined groups. It includes useful utility functions to plot receiver-operator-characteristic, precision-recall and calibration curves, draw stock human figures, estimate counterfactual quantities without the need to re-compute risk scores, to simulate a semi-realistic dataset. Our manuscript can be found at: <doi:10.1371/journal.pdig.0000675>.

r-sop 1.0-1
Propagated dependencies: 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=SOP
Licenses: GPL 2
Build system: r
Synopsis: Generalised Additive P-Spline Regression Models Estimation
Description:

Generalised additive P-spline regression models estimation using the separation of overlapping precision matrices (SOP) method. Estimation is based on the equivalence between P-splines and linear mixed models, and variance/smoothing parameters are estimated based on restricted maximum likelihood (REML). The package enables users to estimate P-spline models with overlapping penalties. Based on the work described in Rodriguez-Alvarez et al. (2015) <doi:10.1007/s11222-014-9464-2>; Rodriguez-Alvarez et al. (2019) <doi:10.1007/s11222-018-9818-2>, and Eilers and Marx (1996) <doi:10.1214/ss/1038425655>.

r-splithalfr 3.0.0
Propagated dependencies: r-tibble@3.3.0 r-rlang@1.1.6 r-psych@2.5.6 r-dplyr@1.1.4 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/tpronk/splithalfr
Licenses: GPL 3
Build system: r
Synopsis: Estimate Split-Half Reliabilities
Description:

Estimates split-half reliabilities for scoring algorithms of cognitive tasks and questionnaires. The splithalfr supports researcher-provided scoring algorithms, with six vignettes illustrating how on included datasets. The package provides four splitting methods (first-second, odd-even, permutated, Monte Carlo), the option to stratify splits by task design, a number of reliability coefficients, the option to sub-sample data, and bootstrapped confidence intervals.

r-super 0.1.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://timtaylor.codeberg.page/super/
Licenses: Expat
Build system: r
Synopsis: Interpreted String Literals
Description:

An implementation of interpreted string literals. Based on the glue package by Hester & Bryan (2024) <doi:10.32614/CRAN.package.glue> but with a focus on efficiency and simplicity at a cost of flexibility.

r-sojourn-data 0.3.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/paulhibbing/Sojourn.Data
Licenses: GPL 3
Build system: r
Synopsis: Supporting Objects for Sojourn Accelerometer Methods
Description:

Stores objects (e.g. neural networks) that are needed for using Sojourn accelerometer methods. For more information, see Lyden K, Keadle S, Staudenmayer J, & Freedson P (2014) <doi:10.1249/MSS.0b013e3182a42a2d>, Ellingson LD, Schwabacher IJ, Kim Y, Welk GJ, & Cook DB (2016) <doi:10.1249/MSS.0000000000000915>, and Hibbing PR, Ellingson LD, Dixon PM, & Welk GJ (2018) <doi:10.1249/MSS.0000000000001486>.

r-sfc 0.1.1
Propagated dependencies: r-zoo@1.8-14 r-triangle@1.0 r-tidyr@1.3.1 r-sna@2.8 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/ctfysh/sfc
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Substance Flow Computation
Description:

This package provides a function sfc() to compute the substance flow with the input files --- "data" and "model". If sample.size is set more than 1, uncertainty analysis will be executed while the distributions and parameters are supplied in the file "data".

r-spas 2025.2.1
Propagated dependencies: r-tmb@1.9.18 r-reshape2@1.4.5 r-rcppeigen@0.3.4.0.2 r-plyr@1.8.9 r-numderiv@2016.8-1.1 r-msm@1.8.2 r-matrix@1.7-4 r-mass@7.3-65 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SPAS
Licenses: GPL 2+
Build system: r
Synopsis: Stratified-Petersen Analysis System
Description:

The Stratified-Petersen Analysis System (SPAS) is designed to estimate abundance in two-sample capture-recapture experiments where the capture and recaptures are stratified. This is a generalization of the simple Lincoln-Petersen estimator. Strata may be defined in time or in space or both, and the s strata in which marking takes place may differ from the t strata in which recoveries take place. When s=t, SPAS reduces to the method described by Darroch (1961) <doi:10.2307/2332748>. When s<t, SPAS implements the methods described in Plante, Rivest, and Tremblay (1988) <doi:10.2307/2533994>. Schwarz and Taylor (1998) <doi:10.1139/f97-238> describe the use of SPAS in estimating return of salmon stratified by time and geography. A related package, BTSPAS, deals with temporal stratification where a spline is used to model the distribution of the population over time as it passes the second capture location. This is the R-version of the (now obsolete) standalone Windows program of the same name.

r-smoothedipw 0.1.0
Propagated dependencies: r-progress@1.2.3 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=smoothedIPW
Licenses: GPL 3+
Build system: r
Synopsis: Time-Smoothed Inverse Probability Weighting for Repeatedly Measured Outcomes
Description:

This package implements several methods to estimate effects of generalized time-varying treatment strategies on the mean of an outcome at one or more selected follow-up times of interest. Specifically, the package implements the time-smoothed inverse probability weighted estimators described in McGrath et al. (2025) <doi:10.48550/arXiv.2509.13971>. Outcomes may be repeatedly, non-monotonically, informatively, and sparsely measured in the data source. The package also supports settings where outcomes are truncated by death, i.e. some individuals die during follow-up which renders the outcome of interest undefined at the follow-up time of interest.

r-saros 1.6.1
Propagated dependencies: r-vctrs@0.6.5 r-tidyselect@1.2.1 r-tidyr@1.3.1 r-stringi@1.8.7 r-rlang@1.1.6 r-officer@0.7.1 r-mschart@0.4.1 r-lifecycle@1.0.4 r-glue@1.8.0 r-ggplot2@4.0.1 r-ggiraph@0.9.2 r-fs@1.6.6 r-forcats@1.0.1 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://nifu-no.github.io/saros/
Licenses: Expat
Build system: r
Synopsis: Semi-Automatic Reporting of Ordinary Surveys
Description:

Offers a systematic way for conditional reporting of figures and tables for many (and bivariate combinations of) variables, typically from survey data. Contains interactive ggiraph'-based (<https://CRAN.R-project.org/package=ggiraph>) plotting functions and data frame-based summary tables (bivariate significance tests, frequencies/proportions, unique open ended responses, etc) with many arguments for customization, and extensions possible. Uses a global options() system for neatly reducing redundant code. Also contains tools for immediate saving of objects and returning a hashed link to the object, useful for creating download links to high resolution images upon rendering in Quarto'. Suitable for highly customized reports, primarily intended for survey research.

r-sfclust 1.0.1
Propagated dependencies: r-stars@0.6-8 r-sparsem@1.84-2 r-sf@1.0-23 r-matrix@1.7-4 r-igraph@2.2.1 r-dplyr@1.1.4 r-cubelyr@1.0.2
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sfclust
Licenses: Expat
Build system: r
Synopsis: Bayesian Spatial Functional Clustering
Description:

Bayesian clustering of spatial regions with similar functional shapes using spanning trees and latent Gaussian models. The method enforces spatial contiguity within clusters and supports a wide range of latent Gaussian models, including non-Gaussian likelihoods, via the R-INLA framework. The algorithm is based on Zhong, R., Chacón-Montalván, E. A., and Moraga, P. (2024) <doi:10.48550/arXiv.2407.12633>, extending the approach of Zhang, B., Sang, H., Luo, Z. T., and Huang, H. (2023) <doi:10.1214/22-AOAS1643>. The package includes tools for model fitting, convergence diagnostics, visualization, and summarization of clustering results.

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