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

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-tidytable 0.11.2
Propagated dependencies: r-vctrs@0.6.5 r-tidyselect@1.2.1 r-rlang@1.1.6 r-pillar@1.11.1 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-glue@1.8.0 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://markfairbanks.github.io/tidytable/
Licenses: Expat
Build system: r
Synopsis: Tidy Interface to 'data.table'
Description:

This package provides a tidy interface to data.table', giving users the speed of data.table while using tidyverse-like syntax.

r-theft 0.8.2
Propagated dependencies: r-tsibble@1.1.6 r-tsfeatures@1.1.1 r-tidyr@1.3.1 r-rlang@1.1.6 r-reticulate@1.44.1 r-rcatch22@0.2.3 r-r-matlab@3.7.0 r-purrr@1.2.0 r-feasts@0.4.2 r-fabletools@0.5.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://hendersontrent.github.io/theft/
Licenses: Expat
Build system: r
Synopsis: Tools for Handling Extraction of Features from Time Series
Description:

Consolidates and calculates different sets of time-series features from multiple R and Python packages including Rcatch22 Henderson, T. (2021) <doi:10.5281/zenodo.5546815>, feasts O'Hara-Wild, M., Hyndman, R., and Wang, E. (2021) <https://CRAN.R-project.org/package=feasts>, tsfeatures Hyndman, R., Kang, Y., Montero-Manso, P., Talagala, T., Wang, E., Yang, Y., and O'Hara-Wild, M. (2020) <https://CRAN.R-project.org/package=tsfeatures>, tsfresh Christ, M., Braun, N., Neuffer, J., and Kempa-Liehr A.W. (2018) <doi:10.1016/j.neucom.2018.03.067>, TSFEL Barandas, M., et al. (2020) <doi:10.1016/j.softx.2020.100456>, and Kats Facebook Infrastructure Data Science (2021) <https://facebookresearch.github.io/Kats/>.

r-taplock 0.2.0
Propagated dependencies: r-tower@0.2.0 r-stringr@1.6.0 r-shiny@1.11.1 r-purrr@1.2.0 r-promises@1.5.0 r-lubridate@1.9.4 r-jose@1.2.1 r-httr2@1.2.1 r-glue@1.8.0 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/ixpantia/tapLock
Licenses: Expat
Build system: r
Synopsis: Seamless Single Sign-on for 'shiny'
Description:

Swift and seamless Single Sign-On (SSO) integration. Designed for effortless compatibility with popular Single Sign-On providers like Google and Microsoft, it streamlines authentication, enhancing both user experience and application security. Elevate your shiny applications for a simplified, unified, and secure authentication process.

r-tikzdevice 0.12.6
Propagated dependencies: r-png@0.1-8 r-filehash@2.4-6
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/daqana/tikzDevice
Licenses: GPL 2+
Build system: r
Synopsis: R Graphics Output in LaTeX Format
Description:

This package provides a graphics output device for R that records plots in a LaTeX-friendly format. The device transforms plotting commands issued by R functions into LaTeX code blocks. When included in a LaTeX document, these blocks are interpreted with the help of TikZ'---a graphics package for TeX and friends written by Till Tantau. Using the tikzDevice', the text of R plots can contain LaTeX commands such as mathematical formula. The device also allows arbitrary LaTeX code to be inserted into the output stream.

r-tsf 0.1.1
Propagated dependencies: r-fracdiff@1.5-3 r-forecast@8.24.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=TSF
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Two Stage Forecasting (TSF) for Long Memory Time Series in Presence of Structural Break
Description:

Forecasting of long memory time series in presence of structural break by using TSF algorithm by Papailias and Dias (2015) <doi:10.1016/j.ijforecast.2015.01.006>.

r-tensorflow 2.20.0
Propagated dependencies: r-yaml@2.3.10 r-tfruns@1.5.4 r-tfautograph@0.3.2 r-rstudioapi@0.17.1 r-reticulate@1.44.1 r-processx@3.8.6 r-lifecycle@1.0.4 r-config@0.3.2
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/rstudio/tensorflow
Licenses: ASL 2.0
Build system: r
Synopsis: R Interface to 'TensorFlow'
Description:

Interface to TensorFlow <https://www.tensorflow.org/>, an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API'. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.

r-tvmvp 1.0.5
Propagated dependencies: r-tidyr@1.3.1 r-r6@2.6.1 r-prettyunits@1.2.0 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/erilill/TV-MVP
Licenses: Expat
Build system: r
Synopsis: Time-Varying Minimum Variance Portfolio
Description:

This package provides the estimation of a time-dependent covariance matrix of returns with the intended use for portfolio optimization. The package offers methods for determining the optimal number of factors to be used in the covariance estimation, a hypothesis test of time-varying covariance, and user-friendly functions for portfolio optimization and rolling window evaluation. The local PCA method, method for determining the number of factors, and associated hypothesis test are based on Su and Wang (2017) <doi:10.1016/j.jeconom.2016.12.004>. The approach to time-varying portfolio optimization follows Fan et al. (2024) <doi:10.1016/j.jeconom.2022.08.007>. The regularisation applied to the residual covariance matrix adopts the technique introduced by Chen et al. (2019) <doi:10.1016/j.jeconom.2019.04.025>.

r-tsintermittent 1.10
Propagated dependencies: r-mapa@2.0.7
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://kourentzes.com/forecasting/2014/06/23/intermittent-demand-forecasting-package-for-r/
Licenses: GPL 2+
Build system: r
Synopsis: Intermittent Time Series Forecasting
Description:

Time series methods for intermittent demand forecasting. Includes Croston's method and its variants (Moving Average, SBA), and the TSB method. Users can obtain optimal parameters on a variety of loss functions, or use fixed ones (Kourenztes (2014) <doi:10.1016/j.ijpe.2014.06.007>). Intermittent time series classification methods and iMAPA that uses multiple temporal aggregation levels are also provided (Petropoulos & Kourenztes (2015) <doi:10.1057/jors.2014.62>).

r-treesim 2.4
Propagated dependencies: r-geiger@2.0.11 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=TreeSim
Licenses: GPL 2
Build system: r
Synopsis: Simulating Phylogenetic Trees
Description:

Simulation methods for phylogenetic trees where (i) all tips are sampled at one time point or (ii) tips are sampled sequentially through time. (i) For sampling at one time point, simulations are performed under a constant rate birth-death process, conditioned on having a fixed number of final tips (sim.bd.taxa()), or a fixed age (sim.bd.age()), or a fixed age and number of tips (sim.bd.taxa.age()). When conditioning on the number of final tips, the method allows for shifts in rates and mass extinction events during the birth-death process (sim.rateshift.taxa()). The function sim.bd.age() (and sim.rateshift.taxa() without extinction) allow the speciation rate to change in a density-dependent way. The LTT plots of the simulations can be displayed using LTT.plot(), LTT.plot.gen() and LTT.average.root(). TreeSim further samples trees with n final tips from a set of trees generated by the common sampling algorithm stopping when a fixed number m>>n of tips is first reached (sim.gsa.taxa()). This latter method is appropriate for m-tip trees generated under a big class of models (details in the sim.gsa.taxa() man page). For incomplete phylogeny, the missing speciation events can be added through simulations (corsim()). (ii) sim.rateshifts.taxa() is generalized to sim.bdsky.stt() for serially sampled trees, where the trees are conditioned on either the number of sampled tips or the age. Furthermore, for a multitype-branching process with sequential sampling, trees on a fixed number of tips can be simulated using sim.bdtypes.stt.taxa(). This function further allows to simulate under epidemiological models with an exposed class. The function sim.genespeciestree() simulates coalescent gene trees within birth-death species trees, and sim.genetree() simulates coalescent gene trees.

r-tfactsr 0.99.0
Propagated dependencies: r-qvalue@2.42.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://afukushima.github.io/TFactSR/
Licenses: GPL 3
Build system: r
Synopsis: Enrichment Approach to Predict Which Transcription Factors are Regulated
Description:

R implementation of TFactS to predict which are the transcription factors (TFs), regulated in a biological condition based on lists of differentially expressed genes (DEGs) obtained from transcriptome experiments. This package is based on the TFactS concept by Essaghir et al. (2010) <doi:10.1093/nar/gkq149> and expands it. It allows users to perform TFactS'-like enrichment approach. The package can import and use the original catalogue file from the TFactS as well as users defined catalogues of interest that are not supported by TFactS (e.g., Arabidopsis).

r-tinflex 2.4
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=Tinflex
Licenses: GPL 2+
Build system: r
Synopsis: Universal Non-Uniform Random Number Generator
Description:

This package provides a universal non-uniform random number generator for quite arbitrary distributions with piecewise twice differentiable densities.

r-tugboat 0.1.6
Propagated dependencies: r-renv@1.1.5 r-here@1.0.2
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://www.dmolitor.com/tugboat/
Licenses: GPL 3+
Build system: r
Synopsis: Build a Docker Image from a Directory or Project
Description:

Simple utilities to generate a Dockerfile from a directory or project, build the corresponding Docker image, push the image to DockerHub, and publicly share the project via Binder.

r-tggd 0.1.3
Propagated dependencies: r-gsl@2.1-9
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tggd
Licenses: GPL 3
Build system: r
Synopsis: The Standard Distribution Functions for the Truncated Generalised Gamma Distribution
Description:

Density, distribution function, quantile function and random generation for the Truncated Generalised Gamma Distribution (also in log10(x) and ln(x) space).

r-tinyshinyserver 0.1.0
Propagated dependencies: r-websocket@1.4.4 r-shiny@1.11.1 r-rmarkdown@2.30 r-quarto@1.5.1 r-openssl@2.3.4 r-logger@0.4.1 r-later@1.4.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-httpuv@1.6.16 r-future@1.68.0 r-digest@0.6.39 r-callr@3.7.6
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/lab1702/tinyshinyserver
Licenses: Expat
Build system: r
Synopsis: Tiny 'shiny' Server - Lightweight Multi-App 'shiny' Proxy
Description:

This package provides a lightweight, WebSocket'-enabled proxy server for hosting multiple shiny applications with automatic health monitoring, session management, and resource cleanup. Provides a simple entry point to run the server using a JSON configuration file.

r-trading 3.2
Propagated dependencies: r-reticulate@1.44.1 r-readxl@1.4.5 r-rcppalgos@2.9.3 r-performanceanalytics@2.0.8 r-ggplot2@4.0.1 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://openriskcalculator.com/
Licenses: GPL 3
Build system: r
Synopsis: Trade Objects, Advanced Correlation & Beta Estimates, Betting Strategies
Description:

This package contains performance analysis metrics of track records including entropy-based correlation and dynamic beta based on a state/space algorithm. The normalized sample entropy method has been implemented which produces accurate entropy estimation even on smaller datasets. On a separate stream, trades from the five major assets classes and also functionality to use pricing curves, rating tables, Credit Support Annex and add-on tables. The implementation follows an object oriented logic whereby each trade inherits from more abstract classes while also the curves/tables are objects. Furthermore, odds calculators and P&L back-testing functionality has been implemented for the most widely used betting/trading strategies including martingale, DAlembert', Labouchere and Fibonacci. Back testing has also been included for the EuroMillions', the EuroJackpot', the UK Lotto, the Set For Life and the UK ThunderBall lotteries. Furthermore, some basic functionality about climate risk has been included.

r-taipan 0.1.2
Propagated dependencies: r-shiny@1.11.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/srkobakian/taipan
Licenses: GPL 3
Build system: r
Synopsis: Tool for Annotating Images in Preparation for Analysis
Description:

This package provides a tool to help create shiny apps for selecting and annotating elements of images. Users must supply images, questions, and answer choices. The user interface is a dynamic shiny app, that displays the images and questions and answer choices. The data generated can be saved to a file that can be used for subsequent analysis. The original purpose was to annotate still images from tennis video for face recognition and emotion detection purposes.

r-tsss 1.3.4-5
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=TSSS
Licenses: GPL 2+
Build system: r
Synopsis: Time Series Analysis with State Space Model
Description:

This package provides functions for statistical analysis, modeling and simulation of time series with state space model, based on the methodology in Kitagawa (2020, ISBN: 978-0-367-18733-0).

r-tidyna 0.4.0
Propagated dependencies: r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/statzhero/tidyna
Licenses: Expat
Build system: r
Synopsis: NA-Aware Defaults for Common R Functions
Description:

This package provides drop-in replacements for common R functions (mean(), sum(), sd(), min(), etc.) that default to na.rm = TRUE and issue warnings when missing values are removed. It handles some special cases. The table() default is set to useNA = ifany'.

r-twowayfeweights 2.0.4
Propagated dependencies: r-rlang@1.1.6 r-magrittr@2.0.4 r-haven@2.5.5 r-fixest@0.13.2 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/chaisemartinPackages
Licenses: Expat
Build system: r
Synopsis: Estimation of the Weights Attached to the Two-Way Fixed Effects Regressions
Description:

Estimates the weights and measure of robustness to treatment effect heterogeneity attached to two-way fixed effects regressions. Clément de Chaisemartin, Xavier D'HaultfŠuille (2020) <DOI: 10.1257/aer.20181169>.

r-trackdf 0.3.3
Propagated dependencies: r-tibble@3.3.0 r-sf@1.0-23 r-lubridate@1.9.4 r-dplyr@1.1.4 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://swarm-lab.github.io/trackdf/
Licenses: GPL 3
Build system: r
Synopsis: Data Frame Class for Tracking Data
Description:

Data frame class for storing collective movement data (e.g. fish schools, ungulate herds, baboon troops) collected from GPS trackers or computer vision tracking software.

r-ttr-pgm 1.0.0
Propagated dependencies: r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-checkmate@2.3.3 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=TTR.PGM
Licenses: LGPL 3
Build system: r
Synopsis: Thornley Transport Resistance Plant Growth Model
Description:

An implementation of the Thornley transport resistance plant growth model. The package can be used to simulate plant growth as forced by climate system variables. The package provides methods for formatting forcing variables, simulating growth dynamics and calibrating model parameters. For more information see Higgins et al. (2025) TTR.PGM: An R package for modelling the distributions and dynamics of plants using the Thornley transport resistance plant growth model. Methods in Ecology and Evolution. in press.

r-tidyaml 0.0.6
Propagated dependencies: r-workflowsets@1.1.1 r-workflows@1.3.0 r-tune@2.0.1 r-tidyr@1.3.1 r-rsample@1.3.1 r-rlang@1.1.6 r-purrr@1.2.0 r-parsnip@1.3.3 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-forcats@1.0.1 r-dplyr@1.1.4 r-broom@1.0.10
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://www.spsanderson.com/tidyAML/
Licenses: Expat
Build system: r
Synopsis: Automatic Machine Learning with 'tidymodels'
Description:

The goal of this package will be to provide a simple interface for automatic machine learning that fits the tidymodels framework. The intention is to work for regression and classification problems with a simple verb framework.

r-tab2xml 1.1.0
Propagated dependencies: r-stringr@1.6.0 r-readxl@1.4.5 r-readods@2.3.2
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://josesamos.github.io/tab2xml/
Licenses: Expat
Build system: r
Synopsis: XML Generation from Tables
Description:

Converting structured data from tables into XML format using predefined templates ensures consistency and flexibility, making it ideal for data exchange, reporting, and automated workflows.

r-tashu 0.1.1
Propagated dependencies: r-reshape2@1.4.5 r-rcolorbrewer@1.1-3 r-randomforest@4.7-1.2 r-plyr@1.8.9 r-lubridate@1.9.4 r-ggplot2@4.0.1 r-drat@0.2.5 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tashu
Licenses: GPL 2+
Build system: r
Synopsis: Analysis and Prediction of Bicycle Rental Amount
Description:

This package provides functions for analyzing citizens bicycle usage pattern and predicting rental amount on specific conditions. Functions on this package interacts with data on tashudata package, a drat repository. tashudata package contains rental/return history on public bicycle system('Tashu'), weather for 3 years and bicycle station information. To install this data package, see the instructions at <https://github.com/zeee1/Tashu_Rpackage>. top10_stations(), top10_paths() function visualizes image showing the most used top 10 stations and paths. daily_bike_rental() and monthly_bike_rental() shows daily, monthly amount of bicycle rental. create_train_dataset(), create_test_dataset() is data processing function for prediction. Bicycle rental history from 2013 to 2014 is used to create training dataset and that on 2015 is for test dataset. Users can make random-forest prediction model by using create_train_model() and predict amount of bicycle rental in 2015 by using predict_bike_rental().

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