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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 search send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.


r-tsibbletalk 0.1.0
Propagated dependencies: r-vctrs@0.7.3 r-tsibble@1.2.0 r-shiny@1.13.0 r-rlang@1.2.0 r-r6@2.6.1 r-plotly@4.12.0 r-lubridate@1.9.5 r-glue@1.8.1 r-dplyr@1.2.1 r-dendextend@1.19.1 r-crosstalk@1.2.2
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tsibbletalk
Licenses: GPL 3
Build system: r
Synopsis: Interactive Graphics for Tsibble Objects
Description:

This package provides a shared tsibble data easily communicates between htmlwidgets on both client and server sides, powered by crosstalk'. A shiny module is provided to visually explore periodic/aperiodic temporal patterns.

r-tidystats 0.7.1
Propagated dependencies: r-jsonlite@2.0.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://willemsleegers.github.io/tidystats/
Licenses: Expat
Build system: r
Synopsis: Save Output of Statistical Tests
Description:

Save the output of statistical tests in an organized file that can be shared with others or used to report statistics in scientific papers.

r-tuckerr-mmgg 1.5.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/gusart/tuckerR_mmgg
Licenses: GPL 3
Build system: r
Synopsis: Three-Mode Principal Components Analysis
Description:

This package performs Three-Mode Principal Components Analysis, which carries out Tucker Models.

r-tree3d 0.1.2
Propagated dependencies: r-rayvertex@0.15.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://tylermorganwall.github.io/tree3d/
Licenses: Expat
Build system: r
Synopsis: 3D Tree Models
Description:

This package provides customizable 3D tree models (as OBJ files) for use in data visualization. Includes both planar and solid tree models, various crown types (columnar, oval, palm, pyramidal, rounded, spreading, vase, weeping), and options to change the diameter, height, and color of the tree's crown and trunk.

r-testassay 0.1.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=testassay
Licenses: Expat
Build system: r
Synopsis: Hypothesis Testing Framework for Validating an Assay for Precision
Description:

This package provides a common way of validating a biological assay for is through a procedure, where m levels of an analyte are measured with n replicates at each level, and if all m estimates of the coefficient of variation (CV) are less than some prespecified level, then the assay is declared validated for precision within the range of the m analyte levels. Two limitations of this procedure are: there is no clear statistical statement of precision upon passing, and it is unclear how to modify the procedure for assays with constant standard deviation. We provide tools to convert such a procedure into a set of m hypothesis tests. This reframing motivates the m:n:q procedure, which upon completion delivers a 100q% upper confidence limit on the CV. Additionally, for a post-validation assay output of y, the method gives an ``effective standard deviation interval of log(y) plus or minus r, which is a 68% confidence interval on log(mu), where mu is the expected value of the assay output for that sample. Further, the m:n:q procedure can be straightforwardly applied to constant standard deviation assays. We illustrate these tools by applying them to a growth inhibition assay. This is an implementation of the methods described in Fay, Sachs, and Miura (2018) <doi:10.1002/sim.7528>.

r-twitteradsr 0.1.0
Propagated dependencies: r-jsonlite@2.0.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://windsor.ai/
Licenses: GPL 3
Build system: r
Synopsis: Get Twitter Ads Data via the 'Windsor.ai' API
Description:

Collect your data on digital marketing campaigns from Twitter Ads using the Windsor.ai API <https://windsor.ai/api-fields/>.

r-taustar 1.1.9
Propagated dependencies: r-rcpparmadillo@15.2.6-1 r-rcpp@1.1.1-1.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/karchjd/TauStar
Licenses: GPL 3+
Build system: r
Synopsis: Efficient Computation and Testing of the Bergsma-Dassios Sign Covariance
Description:

Computes the t* statistic corresponding to the tau* population coefficient introduced by Bergsma and Dassios (2014) <DOI:10.3150/13-BEJ514> and does so in O(n^2) time following the algorithm of Heller and Heller (2016) <DOI:10.48550/arXiv.1605.08732> building off of the work of Weihs, Drton, and Leung (2016) <DOI:10.1007/s00180-015-0639-x>. Also allows for independence testing using the asymptotic distribution of t* as described by Nandy, Weihs, and Drton (2016) <DOI:10.1214/16-EJS1166>.

r-tslstmx 0.1.0
Propagated dependencies: r-tensorflow@2.20.0 r-reticulate@1.46.0 r-keras@2.16.1 r-allmetrics@0.2.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tsLSTMx
Licenses: GPL 3
Build system: r
Synopsis: Predict Time Series Using LSTM Model Including Exogenous Variable to Denote Zero Values
Description:

It is a versatile tool for predicting time series data using Long Short-Term Memory (LSTM) models. It is specifically designed to handle time series with an exogenous variable, allowing users to denote whether data was available for a particular period or not. The package encompasses various functionalities, including hyperparameter tuning, custom loss function support, model evaluation, and one-step-ahead forecasting. With an emphasis on ease of use and flexibility, it empowers users to explore, evaluate, and deploy LSTM models for accurate time series predictions and forecasting in diverse applications. More details can be found in Garai and Paul (2023) <doi:10.1016/j.iswa.2023.200202>.

r-tma 0.3.1
Propagated dependencies: r-rlang@1.2.0 r-rcpparmadillo@15.2.6-1 r-rcpp@1.1.1-1.1 r-data-table@1.18.4
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tma
Licenses: GPL 3
Build system: r
Synopsis: Transmodal Analysis (TMA)
Description:

This package provides a robust computational framework for analyzing complex multimodal data. Extends existing state-dependent models to account for diverse data streams, addressing challenges such as varying temporal scales and learner characteristics to improve the robustness and interpretability of findings. For methodological details, see Shaffer, Wang, and Ruis (2025) "Transmodal Analysis" <doi:10.18608/jla.2025.8423>.

r-tfdeploy 0.6.1
Propagated dependencies: r-tensorflow@2.20.0 r-swagger@5.32.1 r-reticulate@1.46.0 r-magrittr@2.0.5 r-jsonlite@2.0.0 r-httr@1.4.8 r-httpuv@1.6.17
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tfdeploy
Licenses: ASL 2.0
Build system: r
Synopsis: Deploy 'TensorFlow' Models
Description:

This package provides tools to deploy TensorFlow <https://www.tensorflow.org/> models across multiple services. Currently, it provides a local server for testing cloudml compatible services.

r-tscount 1.4.3
Propagated dependencies: r-ltsa@1.4.6.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: http://tscount.r-forge.r-project.org
Licenses: GPL 2 GPL 3
Build system: r
Synopsis: Analysis of Count Time Series
Description:

Likelihood-based methods for model fitting and assessment, prediction and intervention analysis of count time series following generalized linear models are provided. Models with the identity and with the logarithmic link function are allowed. The conditional distribution can be Poisson or Negative Binomial.

r-taskscheduler 1.8
Propagated dependencies: r-data-table@1.18.4
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/bnosac/taskscheduleR
Licenses: AGPL 3
Build system: r
Synopsis: Schedule R Scripts and Processes with the Windows Task Scheduler
Description:

Schedule R scripts/processes with the Windows task scheduler. This allows R users to automate R processes on specific time points from R itself.

r-tempodisco 2.1.0
Propagated dependencies: r-rwiener@1.3-3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://kinleyid.github.io/tempodisco/
Licenses: GPL 3
Build system: r
Synopsis: Temporal Discounting Models
Description:

This package provides tools for working with temporal discounting data, designed for behavioural researchers to simplify data cleaning/scoring and model fitting. The package implements widely used methods such as computing indifference points from adjusting amount task (Frye et al., 2016, <doi:10.3791/53584>), testing for non-systematic discounting per the criteria of Johnson & Bickel (2008, <doi:10.1037/1064-1297.16.3.264>), scoring questionnaires according to the methods of Kirby et al. (1999, <doi:10.1037//0096-3445.128.1.78>) and Wileyto et al (2004, <doi:10.3758/BF03195548>), Bayesian model selection using a range of discount functions (Franck et al., 2015, <doi:10.1002/jeab.128>), drift diffusion models of discounting (Peters & D'Esposito, 2020, <doi:10.1371/journal.pcbi.1007615>), and model-agnostic measures of discounting such as area under the curve (Myerson et al., 2001, <doi:10.1901/jeab.2001.76-235>) and ED50 (Yoon & Higgins, 2008, <doi:10.1016/j.drugalcdep.2007.12.011>).

r-tabula 3.3.2
Propagated dependencies: r-khroma@1.17.0 r-arkhe@1.11.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://codeberg.org/tesselle/tabula
Licenses: GPL 3+
Build system: r
Synopsis: Analysis and Visualization of Archaeological Count Data
Description:

An easy way to examine archaeological count data. This package provides several tests and measures of diversity: heterogeneity and evenness (Brillouin, Shannon, Simpson, etc.), richness and rarefaction (Chao1, Chao2, ACE, ICE, etc.), turnover and similarity (Brainerd-Robinson, etc.). It allows to easily visualize count data and statistical thresholds: rank vs abundance plots, heatmaps, Ford (1962) and Bertin (1977) diagrams, etc.

r-testanaapp 1.1.2
Propagated dependencies: r-tidyr@1.3.2 r-stringr@1.6.0 r-shinydashboard@0.7.3 r-shinycssloaders@1.1.0 r-shiny@1.13.0 r-semplot@1.1.8 r-rmarkdown@2.31 r-plotrix@3.8-14 r-openxlsx@4.2.8.1 r-officer@0.7.5 r-officedown@0.4.1 r-mirt@1.46.1 r-lordif@0.4.2 r-latticeextra@0.6-31 r-golem@0.5.1 r-ggplot2@4.0.3 r-flextable@0.9.11 r-estcrm@1.6 r-dt@0.34.0 r-dplyr@1.2.1 r-difr@6.1.0 r-cowplot@1.2.0 r-brucer@2026.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/jiangyouxiang/TestAnaAPP
Licenses: GPL 3+
Build system: r
Synopsis: 'shiny' App for Test Analysis and Visualization
Description:

This application provides exploratory and confirmatory factor analysis, classical test theory, unidimensional and multidimensional item response theory, and continuous item response model analysis, through the shiny interactive interface. In addition, it offers rich functionalities for visualizing and downloading results. Users can download figures, tables, and analysis reports via the interactive interface.

r-tandem 1.0.3
Propagated dependencies: r-matrix@1.7-5 r-glmnet@5.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=TANDEM
Licenses: GPL 2
Build system: r
Synopsis: Two-Stage Approach to Maximize Interpretability of Drug Response Models Based on Multiple Molecular Data Types
Description:

This package provides a two-stage regression method that can be used when various input data types are correlated, for example gene expression and methylation in drug response prediction. In the first stage it uses the upstream features (such as methylation) to predict the response variable (such as drug response), and in the second stage it uses the downstream features (such as gene expression) to predict the residuals of the first stage. In our manuscript (Aben et al., 2016, <doi:10.1093/bioinformatics/btw449>), we show that using TANDEM prevents the model from being dominated by gene expression and that the features selected by TANDEM are more interpretable.

r-twocoprimary 1.0.0
Propagated dependencies: r-pbivnorm@0.6.0 r-mvtnorm@1.3-7 r-fpcompare@0.2.6
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://gosukehommaex.github.io/twoCoprimary/
Licenses: Expat
Build system: r
Synopsis: Sample Size and Power Calculation for Two Co-Primary Endpoints
Description:

Comprehensive functions to calculate sample size and power for clinical trials with two co-primary endpoints. The package supports five endpoint combinations: two continuous endpoints (Sozu et al. 2011 <doi:10.1080/10543406.2011.551329>), two binary endpoints using asymptotic methods (Sozu et al. 2010 <doi:10.1002/sim.3972>) and exact methods (Homma and Yoshida 2025 <doi:10.1177/09622802251368697>), mixed continuous and binary endpoints (Sozu et al. 2012 <doi:10.1002/bimj.201100221>), and mixed count and continuous endpoints (Homma and Yoshida 2024 <doi:10.1002/pst.2337>). All methods appropriately account for correlation between endpoints and provide both sample size and power calculation capabilities.

r-tokenizers-bpe 0.1.6
Propagated dependencies: r-rcpp@1.1.1-1.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/bnosac/tokenizers.bpe
Licenses: FSDG-compatible
Build system: r
Synopsis: Byte Pair Encoding Text Tokenization
Description:

Unsupervised text tokenizer focused on computational efficiency. Wraps the YouTokenToMe library <https://github.com/VKCOM/YouTokenToMe> which is an implementation of fast Byte Pair Encoding (BPE) <https://aclanthology.org/P16-1162/>.

r-tidydfidx 0.0-3
Propagated dependencies: r-vctrs@0.7.3 r-rdpack@2.6.6 r-pillar@1.11.1 r-dplyr@1.2.1 r-dfidx@0.2-0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tidydfidx
Licenses: GPL 2+
Build system: r
Synopsis: Indexed 'tibble' and Methods for 'dplyr'
Description:

This package provides extended data frames, with a special data frame column which contains two indexes, with potentially a nesting structure, and support for tibbles and methods for dplyr'.

r-twophasegas 1.2.5
Propagated dependencies: r-nloptr@2.2.1 r-matrix@1.7-5 r-mass@7.3-65 r-kofnga@1.3 r-enrichwith@0.5.0 r-dfoptim@2023.1.0 r-data-table@1.18.4
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/egosv/twoPhaseGAS
Licenses: GPL 2+
Build system: r
Synopsis: Two-Phase Genetic Association Study Design and Analysis with Missing Covariates by Design
Description:

This package provides functionality for designing and analysing two-phase genetic association studies. Phase 1 data usually come from genome-wide association study (GWAS) results and we assume phase 2 data will be part of a targeted genome sequencing or fine-mapping study. At design stage, the package assists in selecting a subset of individuals that will be sequenced for phase 2 via alternative approaches, including a flexible genetic algorithm (GA) for near-optimal designs. Once phase 2 data have been collected, the package implements methods to analyse phase 1 and phase 2 data together using semi-parametric regression models via the expectation-maximization (EM) algorithm. For more details see Espin-Garcia, Craiu and Bull (2018) <doi:10.1002/gepi.22099> and Espin-Garcia, Craiu and Bull (2021) <doi:10.1002/sim.9211>.

r-trumpetplots 0.0.1.1
Propagated dependencies: r-purrr@1.2.2 r-magrittr@2.0.5 r-ggplot2@4.0.3 r-data-table@1.18.4
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=TrumpetPlots
Licenses: Expat
Build system: r
Synopsis: Visualization of Genetic Association Studies
Description:

Visualizes the relationship between allele frequency and effect size in genetic association studies. The input is a data frame containing association results. The output is a plot with the effect size of risk variants in the Y axis, and the allele frequency spectrum in the X axis. Corte et al (2023) <doi:10.1101/2023.04.21.23288923>.

r-track2kba 1.1.3
Propagated dependencies: r-tidyr@1.3.2 r-sp@2.2-1 r-sf@1.1-1 r-rlang@1.2.0 r-raster@3.6-32 r-purrr@1.2.2 r-move@4.2.7 r-matching@4.10-15 r-maps@3.4.3 r-magrittr@2.0.5 r-lubridate@1.9.5 r-ggplot2@4.0.3 r-geosphere@1.6-8 r-foreach@1.5.2 r-dplyr@1.2.1 r-adehabitathr@0.4.22
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/BirdLifeInternational/track2kba
Licenses: LGPL 3
Build system: r
Synopsis: Identifying Important Areas from Animal Tracking Data
Description:

This package provides functions for preparing and analyzing animal tracking data, with the intention of identifying areas which are potentially important at the population level and therefore of conservation interest. Areas identified using this package may be checked against global or regionally-defined criteria, such as those set by the Key Biodiversity Area program. The method published herein is described in full in Beal et al. 2021 <doi:10.1111/2041-210X.13713>.

r-tsnet 0.2.0
Propagated dependencies: r-tidyr@1.3.2 r-stanheaders@2.32.10 r-rstantools@2.6.0 r-rstan@2.32.7 r-rlang@1.2.0 r-rcppparallel@5.1.11-2 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.1-1.1 r-posterior@1.7.0 r-loo@2.9.0 r-ggplot2@4.0.3 r-ggokabeito@0.1.0 r-ggdist@3.3.3 r-dplyr@1.2.1 r-cowplot@1.2.0 r-bh@1.90.0-1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/bsiepe/tsnet
Licenses: GPL 3
Build system: r
Synopsis: Fitting, Comparing, and Visualizing Networks Based on Time Series Data
Description:

Fit, compare, and visualize Bayesian graphical vector autoregressive (GVAR) network models using Stan'. These models are commonly used in psychology to represent temporal and contemporaneous relationships between multiple variables in intensive longitudinal data. Fitted models can be compared with a test based on matrix norm differences of posterior point estimates to quantify the differences between two estimated networks. See also Siepe, Kloft & Heck (2024) <doi:10.31234/osf.io/uwfjc>.

r-tabbitr 0.1.3
Propagated dependencies: r-openxlsx@4.2.8.1 r-haven@2.5.5
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/smmcandrew/tabbitR
Licenses: Expat
Build system: r
Synopsis: Weighted Cross-Tabulations Exported to 'Excel'
Description:

This package produces weighted cross-tabulation tables for one or more outcome variables across one or more breakdown variables, and exports them directly to Excel'. For each outcome-by-breakdown combination, the package creates a weighted percentage table and a corresponding unweighted count table, with transparent handling of missing values and light, readable formatting. Designed to support social survey analysis workflows that require large sets of consistent, publication-ready tables.

Total packages: 72693