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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-staggered 1.2.2
Propagated dependencies: r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-purrr@1.2.0 r-mass@7.3-65 r-magrittr@2.0.4 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=staggered
Licenses: GPL 2
Build system: r
Synopsis: Efficient Estimation Under Staggered Treatment Timing
Description:

Efficiently estimates treatment effects in settings with randomized staggered rollouts, using tools proposed by Roth and Sant'Anna (2023) <doi:10.48550/arXiv.2102.01291>.

r-spichanges 0.2.1
Propagated dependencies: r-zoo@1.8-14 r-spsutil@0.2.2.1 r-rlang@1.1.6 r-mumin@1.48.11 r-lubridate@1.9.4 r-gamlss-dist@6.1-1 r-gamlss@5.5-0 r-brglm2@1.0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/gabrielblain/SPIChanges
Licenses: Expat
Build system: r
Synopsis: Improves the Interpretation of the Standardized Precipitation Index Under Changing Climate Conditions
Description:

Improves the interpretation of the Standardized Precipitation Index under changing climate conditions. The package uses the nonstationary approach proposed in Blain et al. (2022) <doi:10.1002/joc.7550> to detect trends in rainfall quantities and to quantify the effect of such trends on the probability of a drought event occurring.

r-starstileserver 0.1.1
Propagated dependencies: r-units@1.0-0 r-stars@0.6-8 r-sf@1.0-23 r-rlang@1.1.6 r-r6@2.6.1 r-png@0.1-8 r-plumber@1.3.0 r-leaflet@2.2.3 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://bartk.gitlab.io/starsTileServer
Licenses: GPL 3
Build system: r
Synopsis: Dynamic Tile Server for R
Description:

Makes it possible to serve map tiles for web maps (e.g. leaflet) based on a function or a stars object without having to render them in advance. This enables parallelization of the rendering, separating the data source and visualization location and to provide web services.

r-stima 1.2.4
Propagated dependencies: r-rpart@4.1.24
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=stima
Licenses: GPL 2
Build system: r
Synopsis: Simultaneous Threshold Interaction Modeling Algorithm
Description:

Regression trunk model estimation proposed by Dusseldorp and Meulman (2004) <doi:10.1007/bf02295641> and Dusseldorp, Conversano, Van Os (2010) <doi:10.1198/jcgs.2010.06089>, integrating a regression tree and a multiple regression model.

r-spnngp 1.0.1
Propagated dependencies: r-rann@2.6.2 r-formula@1.2-5 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://www.finley-lab.com/
Licenses: GPL 2+
Build system: r
Synopsis: Spatial Regression Models for Large Datasets using Nearest Neighbor Gaussian Processes
Description:

Fits univariate Bayesian spatial regression models for large datasets using Nearest Neighbor Gaussian Processes (NNGP) detailed in Finley, Datta, Banerjee (2022) <doi:10.18637/jss.v103.i05>, Finley, Datta, Cook, Morton, Andersen, and Banerjee (2019) <doi:10.1080/10618600.2018.1537924>, and Datta, Banerjee, Finley, and Gelfand (2016) <doi:10.1080/01621459.2015.1044091>.

r-shinybrms 1.8.1
Propagated dependencies: r-shiny@1.11.1 r-rstan@2.32.7 r-rlang@1.1.6 r-brms@2.23.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://fweber144.github.io/shinybrms/
Licenses: GPL 3 FSDG-compatible
Build system: r
Synopsis: Graphical User Interface ('shiny' App) for 'brms'
Description:

This package provides a graphical user interface (GUI) for fitting Bayesian regression models using the package brms which in turn relies on Stan (<https://mc-stan.org/>). The shinybrms GUI is a shiny app.

r-spte2m 1.0.3
Propagated dependencies: r-rmarkdown@2.30 r-mass@7.3-65 r-maps@3.4.3 r-mapproj@1.2.12 r-knitr@1.50 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=SpTe2M
Licenses: GPL 3+
Build system: r
Synopsis: Nonparametric Modeling and Monitoring of Spatio-Temporal Data
Description:

Spatio-temporal data have become increasingly popular in many research fields. Such data often have complex structures that are difficult to describe and estimate. This package provides reliable tools for modeling complicated spatio-temporal data. It also includes tools of online process monitoring to detect possible change-points in a spatio-temporal process over time. More specifically, the package implements the spatio-temporal mean estimation procedure described in Yang and Qiu (2018) <doi:10.1002/sim.7622>, the spatio-temporal covariance estimation procedure discussed in Yang and Qiu (2019) <doi:10.1002/sim.8315>, the three-step method for the joint estimation of spatio-temporal mean and covariance functions suggested by Yang and Qiu (2022) <doi:10.1007/s10463-021-00787-2>, the spatio-temporal disease surveillance method discussed in Qiu and Yang (2021) <doi:10.1002/sim.9150> that can accommodate the covariate effect, the spatial-LASSO-based process monitoring method proposed by Qiu and Yang (2023) <doi:10.1080/00224065.2022.2081104>, and the online spatio-temporal disease surveillance method described in Yang and Qiu (2020) <doi:10.1080/24725854.2019.1696496>.

r-spheresmooth 0.1.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://kybak90.github.io/spheresmooth/
Licenses: GPL 2+
Build system: r
Synopsis: Piecewise Geodesic Smoothing for Spherical Data
Description:

Fitting a smooth path to a given set of noisy spherical data observed at known time points. It implements a piecewise geodesic curve fitting method on the unit sphere based on a velocity-based penalization scheme. The proposed approach is implemented using the Riemannian block coordinate descent algorithm. To understand the method and algorithm, one can refer to Bak, K. Y., Shin, J. K., & Koo, J. Y. (2023) <doi:10.1080/02664763.2022.2054962> for the case of order 1. Additionally, this package includes various functions necessary for handling spherical data.

r-sbde 1.0-2
Propagated dependencies: r-extremefit@1.1.0 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=sbde
Licenses: GPL 2
Build system: r
Synopsis: Semiparametric Bayesian Density Estimation
Description:

Offers Bayesian semiparametric density estimation and tail-index estimation for heavy tailed data, by using a parametric, tail-respecting transformation of the data to the unit interval and then modeling the transformed data with a purely nonparametric logistic Gaussian process density prior. Based on Tokdar et al. (2022) <doi:10.1080/01621459.2022.2104727>.

r-smarteda 0.3.10
Propagated dependencies: r-scales@1.4.0 r-sampling@2.11 r-rmarkdown@2.30 r-qpdf@1.4.1 r-islr@1.4 r-gridextra@2.3 r-ggplot2@4.0.1 r-ggally@2.4.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://daya6489.github.io/SmartEDA/
Licenses: Expat
Build system: r
Synopsis: Summarize and Explore the Data
Description:

Exploratory analysis on any input data describing the structure and the relationships present in the data. The package automatically select the variable and does related descriptive statistics. Analyzing information value, weight of evidence, custom tables, summary statistics, graphical techniques will be performed for both numeric and categorical predictors.

r-singlecellhaystack 1.0.3
Propagated dependencies: r-reshape2@1.4.5 r-matrix@1.7-4 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://alexisvdb.github.io/singleCellHaystack/
Licenses: Expat
Build system: r
Synopsis: Universal Differential Expression Prediction Tool for Single-Cell and Spatial Genomics Data
Description:

One key exploratory analysis step in single-cell genomics data analysis is the prediction of features with different activity levels. For example, we want to predict differentially expressed genes (DEGs) in single-cell RNA-seq data, spatial DEGs in spatial transcriptomics data, or differentially accessible regions (DARs) in single-cell ATAC-seq data. singleCellHaystack predicts differentially active features in single cell omics datasets without relying on the clustering of cells into arbitrary clusters. singleCellHaystack uses Kullback-Leibler divergence to find features (e.g., genes, genomic regions, etc) that are active in subsets of cells that are non-randomly positioned inside an input space (such as 1D trajectories, 2D tissue sections, multi-dimensional embeddings, etc). For the theoretical background of singleCellHaystack we refer to our original paper Vandenbon and Diez (Nature Communications, 2020) <doi:10.1038/s41467-020-17900-3> and our update Vandenbon and Diez (Scientific Reports, 2023) <doi:10.1038/s41598-023-38965-2>.

r-spate 1.7.5
Dependencies: fftw@3.3.10
Propagated dependencies: r-truncnorm@1.0-9 r-mvtnorm@1.3-3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=spate
Licenses: GPL 2
Build system: r
Synopsis: Spatio-Temporal Modeling of Large Data Using a Spectral SPDE Approach
Description:

Functionality for spatio-temporal modeling of large data sets is provided. A Gaussian process in space and time is defined through a stochastic partial differential equation (SPDE). The SPDE is solved in the spectral space, and after discretizing in time and space, a linear Gaussian state space model is obtained. When doing inference, the main computational difficulty consists in evaluating the likelihood and in sampling from the full conditional of the spectral coefficients, or equivalently, the latent space-time process. In comparison to the traditional approach of using a spatio-temporal covariance function, the spectral SPDE approach is computationally advantageous. See Sigrist, Kuensch, and Stahel (2015) <doi:10.1111/rssb.12061> for more information on the methodology. This package aims at providing tools for two different modeling approaches. First, the SPDE based spatio-temporal model can be used as a component in a customized hierarchical Bayesian model (HBM). The functions of the package then provide parameterizations of the process part of the model as well as computationally efficient algorithms needed for doing inference with the HBM. Alternatively, the adaptive MCMC algorithm implemented in the package can be used as an algorithm for doing inference without any additional modeling. The MCMC algorithm supports data that follow a Gaussian or a censored distribution with point mass at zero. Covariates can be included in the model through a regression term.

r-samplesize4clinicaltrials 0.2.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=SampleSize4ClinicalTrials
Licenses: GPL 3
Build system: r
Synopsis: Sample Size Calculation for the Comparison of Means or Proportions in Phase III Clinical Trials
Description:

There are four categories of Phase III clinical trials according to different research goals, including (1) Testing for equality, (2) Superiority trial, (3) Non-inferiority trial, and (4) Equivalence trial. This package aims to help researchers to calculate sample size when comparing means or proportions in Phase III clinical trials with different research goals.

r-scholid 0.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://thomas-rauter.github.io/scholid/
Licenses: Expat
Build system: r
Synopsis: Tools for Scholarly and Academic Identifiers
Description:

This package provides tools for detecting, normalizing, classifying, and extracting scholarly identifier strings. The package provides lightweight, dependency-free helpers for common identifier systems such as DOIs, ORCID iDs, ISBNs, ISSNs, arXiv identifiers, and PubMed identifiers. Functions are designed to be vectorized, predictable, and suitable as low-level building blocks for other R packages and data workflows.

r-safepg 0.0.1
Propagated dependencies: 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=SAFEPG
Licenses: GPL 2
Build system: r
Synopsis: Novel SAFE Model for Predicting Climate-Related Extreme Losses
Description:

The goal of SAFEPG is to predict climate-related extreme losses by fitting a frequency-severity model. It improves predictive performance by introducing a sign-aligned regularization term, which ensures consistent signs for the coefficients across the frequency and severity components. This enhancement not only increases model accuracy but also enhances its interpretability, making it more suitable for practical applications in risk assessment.

r-spmodel 0.12.0
Propagated dependencies: r-tibble@3.3.0 r-sf@1.0-23 r-matrix@1.7-4 r-generics@0.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://usepa.github.io/spmodel/
Licenses: GPL 3
Build system: r
Synopsis: Spatial Statistical Modeling and Prediction
Description:

Fit, summarize, and predict for a variety of spatial statistical models applied to point-referenced and areal (lattice) data. Parameters are estimated using various methods. Additional modeling features include anisotropy, non-spatial random effects, partition factors, big data approaches, and more. Model-fit statistics are used to summarize, visualize, and compare models. Predictions at unobserved locations are readily obtainable. For additional details, see Dumelle et al. (2023) <doi:10.1371/journal.pone.0282524>.

r-shinytoastify 2.0.0
Propagated dependencies: r-shiny@1.11.1 r-reactr@0.6.1 r-htmltools@0.5.8.1 r-fontawesome@0.5.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/stla/shinyToastify
Licenses: GPL 3
Build system: r
Synopsis: Pretty Notifications for 'Shiny'
Description:

This is a wrapper of the React library React-Toastify'. It allows to show some notifications (toasts) in Shiny applications. There are options for the style, the position, the transition effect, and more.

r-sparkavro 0.3.0
Propagated dependencies: r-sparklyr@1.9.3 r-dplyr@1.1.4 r-dbi@1.2.3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sparkavro
Licenses: ASL 2.0 FSDG-compatible
Build system: r
Synopsis: Load Avro file into 'Apache Spark'
Description:

Load Avro Files into Apache Spark using sparklyr'. This allows to read files from Apache Avro <https://avro.apache.org/>.

r-sfadv 1.0.1
Propagated dependencies: r-minpack-lm@1.2-4 r-gmm@1.9-1
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=sfadv
Licenses: GPL 3
Build system: r
Synopsis: Advanced Methods for Stochastic Frontier Analysis
Description:

Stochastic frontier analysis with advanced methods. In particular, it applies the approach proposed by Latruffe et al. (2017) <DOI:10.1093/ajae/aaw077> to estimate a stochastic frontier with technical inefficiency effects when one input is endogenous.

r-smcfcs 2.0.1
Propagated dependencies: r-vgam@1.1-13 r-survival@3.8-3 r-rlang@1.1.6 r-mass@7.3-65 r-checkmate@2.3.3 r-brglm2@1.0.1 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/jwb133/smcfcs
Licenses: GPL 3
Build system: r
Synopsis: Multiple Imputation of Covariates by Substantive Model Compatible Fully Conditional Specification
Description:

This package implements multiple imputation of missing covariates by Substantive Model Compatible Fully Conditional Specification. This is a modification of the popular FCS/chained equations multiple imputation approach, and allows imputation of missing covariate values from models which are compatible with the user specified substantive model.

r-simecol 0.9-3
Propagated dependencies: r-minqa@1.2.8 r-desolve@1.40
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/tpetzoldt/simecol/
Licenses: GPL 2+
Build system: r
Synopsis: Simulation of Ecological (and Other) Dynamic Systems
Description:

An object oriented framework to simulate ecological (and other) dynamic systems. It can be used for differential equations, individual-based (or agent-based) and other models as well. It supports structuring of simulation scenarios (to avoid copy and paste) and aims to improve readability and re-usability of code.

r-scorecardmodelutils 0.0.1.0
Propagated dependencies: r-stringr@1.6.0 r-sqldf@0.4-11 r-reshape2@1.4.5 r-randomforest@4.7-1.2 r-partykit@1.2-24 r-ggplot2@4.0.1 r-gbm@2.2.2 r-e1071@1.7-16 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://cran.r-project.org/package=scorecardModelUtils
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Credit Scorecard Modelling Utils
Description:

This package provides infrastructure functionalities such as missing value treatment, information value calculation, GINI calculation etc. which are used for developing a traditional credit scorecard as well as a machine learning based model. The functionalities defined are standard steps for any credit underwriting scorecard development, extensively used in financial domain.

r-selindrix 0.1.2
Propagated dependencies: r-psych@2.5.6 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/venkatesanraja/seliNDRIx
Licenses: Expat
Build system: r
Synopsis: Construction of Selection Index
Description:

Selection index is one of the efficient and acurrate method for selection of animals. This package is useful for construction of selection indices. It uses mixed and random model least squares analysis to estimate the heritability of traits and genetic correlation between traits. The package uses the sire model as it is considered as random effect. The genetic and phenotypic (co)variances along with the relative economic values are used to construct the selection index for any number of traits. It also estimates the accuracy of the index and the genetic gain expected for different traits. Fisher (1936) <doi:10.1111/j.1469-1809.1936.tb02137.x>.

r-scdeconr 1.0.0
Propagated dependencies: r-seurat@5.3.1 r-reshape2@1.4.5 r-nmf@0.28 r-mgcv@1.9-4 r-matrix@1.7-4 r-mass@7.3-65 r-harmony@1.2.4 r-gtools@3.9.5 r-glmgampoi@1.22.0 r-ggplot2@4.0.1 r-foreach@1.5.2 r-edger@4.8.0 r-dplyr@1.1.4 r-data-table@1.17.8 r-biobase@2.70.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/Liuy12/SCdeconR/
Licenses: GPL 3+
Build system: r
Synopsis: Deconvolution of Bulk RNA-Seq Data using Single-Cell RNA-Seq Data as Reference
Description:

Streamlined workflow from deconvolution of bulk RNA-seq data to downstream differential expression and gene-set enrichment analysis. Provide various visualization functions.

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