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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-sharperratio 1.4.3
Propagated dependencies: r-rcpp@1.1.0 r-ghyp@1.6.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sharpeRratio
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Moment-Free Estimation of Sharpe Ratios
Description:

An efficient moment-free estimator of the Sharpe ratio, or signal-to-noise ratio, for heavy-tailed data (see <arXiv:1505.01333>).

r-sta 0.1.7
Propagated dependencies: r-trend@1.1.6 r-rcolorbrewer@1.1-3 r-raster@3.6-32 r-mapview@2.11.4 r-geots@0.1.10 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=sta
Licenses: GPL 2+
Build system: r
Synopsis: Seasonal Trend Analysis for Time Series Imagery in R
Description:

Efficiently estimate shape parameters of periodic time series imagery with which a statistical seasonal trend analysis (STA) is subsequently performed. STA output can be exported in conventional raster formats. Methods to visualize STA output are also implemented as well as the calculation of additional basic statistics. STA is based on (R. Eastman, F. Sangermano, B. Ghimire, H. Zhu, H. Chen, N. Neeti, Y. Cai, E. Machado and S. Crema, 2009) <doi:10.1080/01431160902755338>.

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-survc 0.1.0
Propagated dependencies: r-timeroc@0.4 r-survival@3.8-3 r-rvg@0.4.1 r-officer@0.7.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://newjoseph.github.io/survC/
Licenses: Expat
Build system: r
Synopsis: Survival Model Validation Utilities
Description:

This package provides helper functions to compute linear predictors, time-dependent ROC curves, and Harrell's concordance index for Cox proportional hazards models as described in Therneau (2024) <https://CRAN.R-project.org/package=survival>, Therneau and Grambsch (2000, ISBN:0-387-98784-3), Hung and Chiang (2010) <doi:10.1002/cjs.10046>, Uno et al. (2007) <doi:10.1198/016214507000000149>, Blanche, Dartigues, and Jacqmin-Gadda (2013) <doi:10.1002/sim.5958>, Blanche, Latouche, and Viallon (2013) <doi:10.1007/978-1-4614-8981-8_11>, Harrell et al. (1982) <doi:10.1001/jama.1982.03320430047030>, Peto and Peto (1972) <doi:10.2307/2344317>, Schemper (1992) <doi:10.2307/2349009>, and Uno et al. (2011) <doi:10.1002/sim.4154>.

r-speck 1.0.1
Propagated dependencies: r-seurat@5.3.1 r-rsvd@1.0.5 r-matrix@1.7-4 r-magrittr@2.0.4 r-ckmeans-1d-dp@4.3.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SPECK
Licenses: GPL 2+
Build system: r
Synopsis: Receptor Abundance Estimation using Reduced Rank Reconstruction and Clustered Thresholding
Description:

Surface Protein abundance Estimation using CKmeans-based clustered thresholding ('SPECK') is an unsupervised learning-based method that performs receptor abundance estimation for single cell RNA-sequencing data based on reduced rank reconstruction (RRR) and a clustered thresholding mechanism. Seurat's normalization method is described in: Hao et al., (2021) <doi:10.1016/j.cell.2021.04.048>, Stuart et al., (2019) <doi:10.1016/j.cell.2019.05.031>, Butler et al., (2018) <doi:10.1038/nbt.4096> and Satija et al., (2015) <doi:10.1038/nbt.3192>. Method for the RRR is further detailed in: Erichson et al., (2019) <doi:10.18637/jss.v089.i11> and Halko et al., (2009) <doi:10.48550/arXiv.0909.4061>. Clustering method is outlined in: Song et al., (2020) <doi:10.1093/bioinformatics/btaa613> and Wang et al., (2011) <doi:10.32614/RJ-2011-015>.

r-sptimer 3.3.3
Propagated dependencies: r-spacetime@1.3-3 r-sp@2.2-0 r-extradistr@1.10.0 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=spTimer
Licenses: GPL 2+
Build system: r
Synopsis: Spatio-Temporal Bayesian Modelling
Description:

Fits, spatially predicts and temporally forecasts large amounts of space-time data using [1] Bayesian Gaussian Process (GP) Models, [2] Bayesian Auto-Regressive (AR) Models, and [3] Bayesian Gaussian Predictive Processes (GPP) based AR Models for spatio-temporal big-n problems. Bakar and Sahu (2015) <doi:10.18637/jss.v063.i15>.

r-shinylogs 0.2.1
Propagated dependencies: r-shiny@1.11.1 r-nanotime@0.3.12 r-jsonlite@2.0.0 r-htmltools@0.5.8.1 r-digest@0.6.39 r-data-table@1.17.8 r-bit64@4.6.0-1 r-anytime@0.3.12
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/dreamRs/shinylogs
Licenses: GPL 3
Build system: r
Synopsis: Record Everything that Happens in a 'Shiny' Application
Description:

Track and record the use of applications and the user's interactions with Shiny inputs. Allows to trace the inputs with which the user interacts, the outputs generated, as well as the errors displayed in the interface.

r-soptdmaea 1.0.1
Propagated dependencies: r-matrix@1.7-4 r-mass@7.3-65 r-igraph@2.2.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=soptdmaeA
Licenses: GPL 2
Build system: r
Synopsis: Sequential Optimal Designs for Two-Colour cDNA Microarray Experiments
Description:

Computes sequential A-, MV-, D- and E-optimal or near-optimal block and row-column designs for two-colour cDNA microarray experiments using the linear fixed effects and mixed effects models where the interest is in a comparison of all possible elementary treatment contrasts. The package also provides an optional method of using the graphical user interface (GUI) R package tcltk to ensure that it is user friendly.

r-straweib 1.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=straweib
Licenses: GPL 2+
Build system: r
Synopsis: Stratified Weibull Regression Model
Description:

The main function is icweib(), which fits a stratified Weibull proportional hazards model for left censored, right censored, interval censored, and non-censored survival data. We parameterize the Weibull regression model so that it allows a stratum-specific baseline hazard function, but where the effects of other covariates are assumed to be constant across strata. Please refer to Xiangdong Gu, David Shapiro, Michael D. Hughes and Raji Balasubramanian (2014) <doi:10.32614/RJ-2014-003> for more details.

r-simtool 1.1.9
Propagated dependencies: r-vctrs@0.6.5 r-tidyr@1.3.1 r-tibble@3.3.0 r-purrr@1.2.0 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://marselscheer.github.io/simTool/
Licenses: GPL 3
Build system: r
Synopsis: Conduct Simulation Studies with a Minimal Amount of Source Code
Description:

Tool for statistical simulations that have two components. One component generates the data and the other one analyzes the data. The main aims of the package are the reduction of the administrative source code (mainly loops and management code for the results) and a simple applicability of the package that allows the user to quickly learn how to work with it. Parallel computing is also supported. Finally, convenient functions are provided to summarize the simulation results.

r-spnaf 1.1.0
Propagated dependencies: r-tidyr@1.3.1 r-spdep@1.4-1 r-sf@1.0-23 r-rlang@1.1.6 r-magrittr@2.0.4 r-dplyr@1.1.4 r-deldir@2.0-4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=spnaf
Licenses: Expat
Build system: r
Synopsis: Spatial Network Autocorrelation for Flow Data
Description:

Identify statistically significant flow clusters using the local spatial network autocorrelation statistic G_ij* proposed by Berglund and Karlström (1999) <doi:10.1007/s101090050013>. The metric, an extended statistic of Getis/Ord G ('Getis and Ord 1992) <doi:10.1111/j.1538-4632.1992.tb00261.x>, detects a group of flows having similar traits in terms of directionality. You provide OD data and the associated polygon to get results with several parameters, some of which are defined by spdep package.

r-sommer 4.4.4
Propagated dependencies: r-rcppprogress@0.4.2 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-matrix@1.7-4 r-mass@7.3-65 r-enhancer@1.1.0 r-crayon@1.5.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/covaruber/sommer
Licenses: GPL 2+
Build system: r
Synopsis: Solving Mixed Model Equations in R
Description:

Structural multivariate-univariate linear mixed model solver for estimation of multiple random effects with unknown variance-covariance structures (e.g., heterogeneous and unstructured) and known covariance among levels of random effects (e.g., pedigree and genomic relationship matrices) (Covarrubias-Pazaran, 2016 <doi:10.1371/journal.pone.0156744>; Maier et al., 2015 <doi:10.1016/j.ajhg.2014.12.006>; Jensen et al., 1997). REML estimates can be obtained using the Direct-Inversion Newton-Raphson and Direct-Inversion Average Information algorithms for the problems r x r (r being the number of records) or using the Henderson-based average information algorithm for the problem c x c (c being the number of coefficients to estimate). Spatial models can also be fitted using the two-dimensional spline functionality available.

r-swarmverse 0.1.1
Propagated dependencies: r-trackdf@0.3.3 r-swarm@0.6.0 r-rtsne@0.17 r-pbapply@1.7-4 r-geosphere@1.5-20
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://marinapapa.github.io/swaRmverse/
Licenses: GPL 3
Build system: r
Synopsis: Swarm Space Creation
Description:

This package provides a pipeline for the comparative analysis of collective movement data (e.g. fish schools, bird flocks, baboon troops) by processing 2-dimensional positional data (x,y,t) from GPS trackers or computer vision tracking systems, discretizing events of collective motion, calculating a set of established metrics that characterize each event, and placing the events in a multi-dimensional swarm space constructed from these metrics. The swarm space concept, the metrics and data sets included are described in: Papadopoulou Marina, Furtbauer Ines, O'Bryan Lisa R., Garnier Simon, Georgopoulou Dimitra G., Bracken Anna M., Christensen Charlotte and King Andrew J. (2023) <doi:10.1098/rstb.2022.0068>.

r-slackr 3.3.1
Propagated dependencies: r-withr@3.0.2 r-tibble@3.3.0 r-rlang@1.1.6 r-memoise@2.0.1 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-dplyr@1.1.4 r-cachem@1.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/mrkaye97/slackr
Licenses: Expat
Build system: r
Synopsis: Send Messages, Images, R Objects and Files to 'Slack' Channels/Users
Description:

Slack <https://slack.com/> provides a service for teams to collaborate by sharing messages, images, links, files and more. Functions are provided that make it possible to interact with the Slack platform API'. When you need to share information or data from R, rather than resort to copy/ paste in e-mails or other services like Skype <https://www.skype.com/en/>, you can use this package to send well-formatted output from multiple R objects and expressions to all teammates at the same time with little effort. You can also send images from the current graphics device, R objects, and upload files.

r-sightabilitymodel 1.5.5
Propagated dependencies: r-survey@4.4-8 r-plyr@1.8.9 r-mvtnorm@1.3-3 r-msm@1.8.2 r-matrix@1.7-4 r-formula-tools@1.7.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/jfieberg/SightabilityModel
Licenses: GPL 2
Build system: r
Synopsis: Wildlife Sightability Modeling
Description:

Uses logistic regression to model the probability of detection as a function of covariates. This model is then used with observational survey data to estimate population size, while accounting for uncertain detection. See Steinhorst and Samuel (1989).

r-spbayessurv 1.1.9
Propagated dependencies: r-survival@3.8-3 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mass@7.3-65 r-fields@17.1 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=spBayesSurv
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Modeling and Analysis of Spatially Correlated Survival Data
Description:

This package provides several Bayesian survival models for spatial/non-spatial survival data: proportional hazards (PH), accelerated failure time (AFT), proportional odds (PO), and accelerated hazards (AH), a super model that includes PH, AFT, PO and AH as special cases, Bayesian nonparametric nonproportional hazards (LDDPM), generalized accelerated failure time (GAFT), and spatially smoothed Polya tree density estimation. The spatial dependence is modeled via frailties under PH, AFT, PO, AH and GAFT, and via copulas under LDDPM and PH. Model choice is carried out via the logarithm of the pseudo marginal likelihood (LPML), the deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). See Zhou, Hanson and Zhang (2020) <doi:10.18637/jss.v092.i09>.

r-saros-base 1.2.0
Propagated dependencies: r-zip@2.3.3 r-yaml@2.3.10 r-vctrs@0.6.5 r-tidyselect@1.2.1 r-tidyr@1.3.1 r-stringi@1.8.7 r-rstudioapi@0.17.1 r-rlang@1.1.6 r-glue@1.8.0 r-fs@1.6.6 r-forcats@1.0.1 r-dplyr@1.1.4 r-cli@3.6.5 r-bcrypt@1.2.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://nifu-no.github.io/saros.base/
Licenses: Expat
Build system: r
Synopsis: Base Tools for Semi-Automatic Reporting of Ordinary Surveys
Description:

Scaffold an entire web-based report using template chunks, based on a small chapter overview and a dataset. Highly adaptable with prefixes, suffixes, translations, etc. Also contains tools for password-protecting, e.g. for each organization's report on a website. Developed for the common case of a survey across multiple organizations/sites where each organization wants to obtain results for their organization compared with everyone else. See saros (<https://CRAN.R-project.org/package=saros>) for tools used for authors in the drafted reports.

r-survivalsurrogate 1.1
Propagated dependencies: r-sparsem@1.84-2 r-rpart@4.1.24 r-rbeta2009@1.0.1 r-purrr@1.2.0 r-mlr3@1.2.0 r-magrittr@2.0.4 r-glue@1.8.0 r-dplyr@1.1.4 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=survivalsurrogate
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Evaluate a Longitudinal Surrogate with a Censored Outcome
Description:

This package provides influence function-based methods to evaluate a longitudinal surrogate marker in a censored time-to-event outcome setting, with plug-in and targeted maximum likelihood estimation options. Details are described in: Agniel D and Parast L (2025). "Robust Evaluation of Longitudinal Surrogate Markers with Censored Data." Journal of the Royal Statistical Society: Series B <doi:10.1093/jrsssb/qkae119>. A tutorial for this package can be found at <https://www.laylaparast.com/survivalsurrogate> and a Shiny App implementing the package can be found at <https://parastlab.shinyapps.io/survivalsurrogateApp/>.

r-season 0.3.16
Propagated dependencies: r-survival@3.8-3 r-stringr@1.6.0 r-mass@7.3-65 r-ggplot2@4.0.1 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/agbarnett/season
Licenses: GPL 3+
Build system: r
Synopsis: Seasonal Analysis of Health Data
Description:

Routines for the seasonal analysis of health data, including regression models, time-stratified case-crossover, plotting functions and residual checks, see Barnett and Dobson (2010) ISBN 978-3-642-10748-1. Thanks to Yuming Guo for checking the case-crossover code.

r-sugarglider 1.0.3
Propagated dependencies: 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://maliny12.github.io/sugarglider/
Licenses: Expat
Build system: r
Synopsis: Create Glyph-Maps of Spatiotemporal Data
Description:

This package provides ggplot2 extensions to construct glyph-maps for visualizing seasonality in spatiotemporal data. See the Journal of Statistical Software reference: Zhang, H. S., Cook, D., Laa, U., Langrené, N., & Menéndez, P. (2024) <doi:10.18637/jss.v110.i07>. The manuscript for this package is currently under preparation and can be found on GitHub at <https://github.com/maliny12/paper-sugarglider>.

r-svenssonm 0.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=svenssonm
Licenses: GPL 3
Build system: r
Synopsis: Svensson's Method
Description:

Obtain parameters of Svensson's Method, including percentage agreement, systematic change and individual change. Also, the contingency table can be generated. Svensson's Method is a rank-invariant nonparametric method for the analysis of ordered scales which measures the level of change both from systematic and individual aspects. For the details, please refer to Svensson E. Analysis of systematic and random differences between paired ordinal categorical data [dissertation]. Stockholm: Almqvist & Wiksell International; 1993.

r-shiftr 1.5
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/andreyshabalin/shiftR
Licenses: LGPL 3
Build system: r
Synopsis: Fast Enrichment Analysis via Circular Permutations
Description:

Fast enrichment analysis for locally correlated statistics via circular permutations. The analysis can be performed at multiple significance thresholds for both primary and auxiliary data sets with efficient correction for multiple testing.

r-splitselect 1.0.3
Propagated dependencies: r-multicool@1.0.1 r-glmnet@4.1-10 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=splitSelect
Licenses: GPL 2+
Build system: r
Synopsis: Best Split Selection Modeling for Low-Dimensional Data
Description:

This package provides functions to generate or sample from all possible splits of features or variables into a number of specified groups. Also computes the best split selection estimator (for low-dimensional data) as defined in Christidis, Van Aelst and Zamar (2019) <arXiv:1812.05678>.

r-seqmade 1.0
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=SeqMADE
Licenses: GPL 2+
Build system: r
Synopsis: Network Module-Based Model in the Differential Expression Analysis for RNA-Seq
Description:

This package provides a network module-based generalized linear model for differential expression analysis with the count-based sequence data from RNA-Seq.

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