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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-tmcn 0.2-13
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tmcn
Licenses: LGPL 2.0+
Build system: r
Synopsis: Text Mining Toolkit for Chinese
Description:

This package provides a Text mining toolkit for Chinese, which includes facilities for Chinese string processing, Chinese NLP supporting, encoding detecting and converting. Moreover, it provides some functions to support tm package in Chinese.

r-thredds 0.1-4
Propagated dependencies: r-xml2@1.5.0 r-rlang@1.1.6 r-r6@2.6.1 r-magrittr@2.0.4 r-httr@1.4.7
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/BigelowLab/thredds
Licenses: Expat
Build system: r
Synopsis: Crawler for Navigating THREDDS Catalogs
Description:

This package provides a crawler for programmatically navigating THREDDS Data Server (<https://www.unidata.ucar.edu/software/tds/>) catalogs, and access dataset metadata and resources.

r-tricolore 1.2.6
Propagated dependencies: r-shiny@1.11.1 r-rlang@1.1.6 r-ggtern@4.0.0 r-ggplot2@4.0.1 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/jschoeley/tricolore
Licenses: GPL 3
Build system: r
Synopsis: Flexible Color Scale for Ternary Compositions
Description:

Compositional data consisting of three-parts can be color mapped with a ternary color scale. Such a scale is provided by the tricolore packages with options for discrete and continuous colors, mean-centering and scaling. See Jonas Schöley (2021) "The centered ternary balance scheme. A technique to visualize surfaces of unbalanced three-part compositions" <doi:10.4054/DemRes.2021.44.19>, Jonas Schöley, Frans Willekens (2017) "Visualizing compositional data on the Lexis surface" <doi:10.4054/DemRes.2017.36.21>, and Ilya Kashnitsky, Jonas Schöley (2018) "Regional population structures at a glance" <doi:10.1016/S0140-6736(18)31194-2>.

r-tsissm 1.0.2
Propagated dependencies: r-zoo@1.8-14 r-xts@0.14.1 r-viridislite@0.4.2 r-tsmethods@1.0.2 r-tsdistributions@1.0.3 r-tsaux@1.0.0 r-tmb@1.9.18 r-sandwich@3.1-1 r-rtmb@1.8 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-progressr@0.18.0 r-nloptr@2.2.1 r-future-apply@1.20.0 r-future@1.68.0 r-flextable@0.9.10 r-data-table@1.17.8 r-copula@1.1-6
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/tsmodels/tsissm
Licenses: GPL 2
Build system: r
Synopsis: Linear Innovations State Space Unobserved Components Model
Description:

Unobserved components time series model using the linear innovations state space representation (single source of error) with choice of error distributions and option for dynamic variance. Methods for estimation using automatic differentiation, automatic model selection and ensembling, prediction, filtering, simulation and backtesting. Based on the model described in Hyndman et al (2012) <doi:10.1198/jasa.2011.tm09771>.

r-ttutils 1.0-1.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=ttutils
Licenses: GPL 2
Build system: r
Synopsis: Utility Functions
Description:

This package contains some auxiliary functions.

r-tlda 0.1.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/lsoenning/tlda
Licenses: Expat
Build system: r
Synopsis: Tools for Language Data Analysis
Description:

Support functions and datasets to facilitate the analysis of linguistic data. The current focus is on the calculation of corpus-linguistic dispersion measures as described in Gries (2021) <doi:10.1007/978-3-030-46216-1_5> and Soenning (2025) <doi:10.3366/cor.2025.0326>. The most commonly used parts-based indices are implemented, including different formulas and modifications that are found in the literature, with the additional option to obtain frequency-adjusted scores. Dispersion scores can be computed based on individual count variables or a term-document matrix.

r-tcpl 3.3.1
Propagated dependencies: r-viridis@0.6.5 r-tidyr@1.3.1 r-tcplfit2@0.1.9 r-stringr@1.6.0 r-sqldf@0.4-11 r-rmariadb@1.3.4 r-rlang@1.1.6 r-rcolorbrewer@1.1-3 r-plotly@4.11.0 r-numderiv@2016.8-1.1 r-gt@1.3.0 r-gridextra@2.3 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-dbi@1.2.3 r-data-table@1.17.8 r-ctxr@1.1.3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/USEPA/CompTox-ToxCast-tcpl
Licenses: Expat
Build system: r
Synopsis: ToxCast Data Analysis Pipeline
Description:

The ToxCast Data Analysis Pipeline ('tcpl') is an R package that manages, curve-fits, plots, and stores ToxCast data to populate its linked MySQL database, invitrodb'. The package was developed for the chemical screening data curated by the US EPA's Toxicity Forecaster (ToxCast) program, but tcpl can be used to support diverse chemical screening efforts.

r-twfeivdecomp 0.1.0
Propagated dependencies: r-magrittr@2.0.4 r-formula@1.2-5 r-dplyr@1.1.4 r-aer@1.2-15
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/shomiyaji/twfeiv-decomp
Licenses: Expat
Build system: r
Synopsis: Instrumented Difference-in-Differences Decomposition
Description:

This package implements a decomposition of the two-way fixed effects instrumental variable estimator into all possible Wald difference-in-differences estimators. Provides functions to summarize the contribution of different cohort comparisons to the overall two-way fixed effects instrumental variable estimate, with or without controls. The method is described in Miyaji (2024) <doi:10.48550/arXiv.2405.16467>.

r-tssmoothing 0.1.0
Propagated dependencies: r-matrix@1.7-4 r-mass@7.3-65 r-gridextra@2.3 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=TSsmoothing
Licenses: GPL 3
Build system: r
Synopsis: Trend Estimation of Univariate and Bivariate Time Series with Controlled Smoothness
Description:

It performs the smoothing approach provided by penalized least squares for univariate and bivariate time series, as proposed by Guerrero (2007) and Gerrero et al. (2017). This allows to estimate the time series trend by controlling the amount of resulting (joint) smoothness. --- Guerrero, V.M (2007) <DOI:10.1016/j.spl.2007.03.006>. Guerrero, V.M; Islas-Camargo, A. and Ramirez-Ramirez, L.L. (2017) <DOI:10.1080/03610926.2015.1133826>.

r-topdowntimeratio 0.1.0
Propagated dependencies: r-magrittr@2.0.4 r-lubridate@1.9.4 r-geodist@0.1.1 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=topdowntimeratio
Licenses: GPL 3+
Build system: r
Synopsis: Top-Down Time Ratio Segmentation for Coordinate Trajectories
Description:

Data collected on movement behavior is often in the form of time- stamped latitude/longitude coordinates sampled from the underlying movement behavior. These data can be compressed into a set of segments via the Top- Down Time Ratio Segmentation method described in Meratnia and de By (2004) <doi:10.1007/978-3-540-24741-8_44> which, with some loss of information, can both reduce the size of the data as well as provide corrective smoothing mechanisms to help reduce the impact of measurement error. This is an improvement on the well-known Douglas-Peucker algorithm for segmentation that operates not on the basis of perpendicular distances. Top-Down Time Ratio segmentation allows for disparate sampling time intervals by calculating the distance between locations and segments with respect to time. Provided a trajectory with timestamps, tdtr() returns a set of straight- line segments that can represent the full trajectory. McCool, Lugtig, and Schouten (2022) <doi:10.1007/s11116-022-10328-2> describe this method as implemented here in more detail.

r-trimatch 1.0.1
Propagated dependencies: r-stringr@1.6.0 r-scales@1.4.0 r-reshape2@1.4.5 r-randomforest@4.7-1.2 r-psych@2.5.6 r-psagraphics@2.1.3 r-plyr@1.8.9 r-gridextra@2.3 r-ggplot2@4.0.1 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://jbryer.github.io/TriMatch/
Licenses: GPL 2+
Build system: r
Synopsis: Propensity Score Matching of Non-Binary Treatments
Description:

Propensity score matching for non-binary treatments.

r-tfprobability 0.15.2
Propagated dependencies: r-tensorflow@2.20.0 r-reticulate@1.44.1 r-magrittr@2.0.4 r-keras@2.16.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/rstudio/tfprobability
Licenses: ASL 2.0
Build system: r
Synopsis: Interface to 'TensorFlow Probability'
Description:

Interface to TensorFlow Probability', a Python library built on TensorFlow that makes it easy to combine probabilistic models and deep learning on modern hardware ('TPU', GPU'). TensorFlow Probability includes a wide selection of probability distributions and bijectors, probabilistic layers, variational inference, Markov chain Monte Carlo, and optimizers such as Nelder-Mead, BFGS, and SGLD.

r-teal-data 0.8.0
Propagated dependencies: r-teal-code@0.7.1 r-rlang@1.1.6 r-lifecycle@1.0.4 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://insightsengineering.github.io/teal.data/
Licenses: ASL 2.0
Build system: r
Synopsis: Data Model for 'teal' Applications
Description:

This package provides a teal_data class as a unified data model for teal applications focusing on reproducibility and relational data.

r-tsutils 0.9.4
Propagated dependencies: r-rcolorbrewer@1.1-3 r-plotrix@3.8-13 r-mapa@2.0.7 r-forecast@8.24.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/trnnick/tsutils/
Licenses: GPL 3
Build system: r
Synopsis: Time Series Exploration, Modelling and Forecasting
Description:

Includes: (i) tests and visualisations that can help the modeller explore time series components and perform decomposition; (ii) modelling shortcuts, such as functions to construct lagmatrices and seasonal dummy variables of various forms; (iii) an implementation of the Theta method; (iv) tools to facilitate the design of the forecasting process, such as ABC-XYZ analyses; and (v) "quality of life" functions, such as treating time series for trailing and leading values.

r-tfrmt 0.3.0
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-stringi@1.8.7 r-rlang@1.1.6 r-purrr@1.2.0 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-gt@1.3.0 r-glue@1.8.0 r-ggplot2@4.0.1 r-forcats@1.0.1 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://GSK-Biostatistics.github.io/tfrmt/
Licenses: FSDG-compatible
Build system: r
Synopsis: Applies Display Metadata to Analysis Results Datasets
Description:

This package creates a framework to store and apply display metadata to Analysis Results Datasets (ARDs). The use of tfrmt allows users to define table format and styling without the data, and later apply the format to the data.

r-thresholdrocsurvival 1.2.1
Propagated dependencies: r-thresholdroc@2.9.5 r-survival@3.8-3 r-psych@2.5.6 r-proc@1.19.0.1 r-informativecensoring@0.3.6 r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=ThresholdROCsurvival
Licenses: GPL 2+
Build system: r
Synopsis: Diagnostic Ability Assessment with Right-Censored Data at a Fixed Time t
Description:

We focus on the diagnostic ability assessment of medical tests when the outcome of interest is the status (alive or dead) of the subjects at a certain time-point t. This binary status is determined by right-censored times to event and it is unknown for those subjects censored before t. Here we provide three methods (unknown status exclusion, imputation of censored times and using time-dependent ROC curves) to evaluate the diagnostic ability of binary and continuous tests in this context. Two references for the methods used here are Skaltsa et al. (2010) <doi:10.1002/bimj.200900294> and Heagerty et al. (2000) <doi:10.1111/j.0006-341x.2000.00337.x>.

r-t4transport 0.1.8
Propagated dependencies: r-rdpack@2.6.4 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://www.kisungyou.com/T4transport/
Licenses: Expat
Build system: r
Synopsis: Tools for Computational Optimal Transport
Description:

Transport theory has seen much success in many fields of statistics and machine learning. We provide a variety of algorithms to compute Wasserstein distance, barycenter, and others. See Peyré and Cuturi (2019) <doi:10.1561/2200000073> for the general exposition to the study of computational optimal transport.

r-thames 0.1.2
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=thames
Licenses: GPL 3+
Build system: r
Synopsis: Truncated Harmonic Mean Estimator of the Marginal Likelihood
Description:

This package implements the truncated harmonic mean estimator (THAMES) of the reciprocal marginal likelihood using posterior samples and unnormalized log posterior values via reciprocal importance sampling. Metodiev, Perrot-Dockès, Ouadah, Irons, Latouche, & Raftery (2024). Bayesian Analysis. <doi:10.1214/24-BA1422>.

r-tpfp 0.0.1
Propagated dependencies: r-xlsx@0.6.5 r-readxl@1.4.5 r-knitr@1.50
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tpfp
Licenses: Expat
Build system: r
Synopsis: Counts the Number of True Positives and False Positives
Description:

Calculates the number of true positives and false positives from a dataset formatted for Jackknife alternative free-response receiver operating characteristic which is used for statistical analysis which is explained in the book Chakraborty DP (2017), "Observer Performance Methods for Diagnostic Imaging - Foundations, Modeling, and Applications with R-Based Examples", Taylor-Francis <https://www.crcpress.com/9781482214840>.

r-tlm 0.2.0
Propagated dependencies: r-boot@1.3-32
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tlm
Licenses: GPL 3+
Build system: r
Synopsis: Effects under Linear, Logistic and Poisson Regression Models with Transformed Variables
Description:

Computation of effects under linear, logistic and Poisson regression models with transformed variables. Logarithm and power transformations are allowed. Effects can be displayed both numerically and graphically in both the original and the transformed space of the variables. The methods are described in Barrera-Gomez and Basagana (2015) <doi:10.1097/EDE.0000000000000247>.

r-traveltimer 1.3.1
Propagated dependencies: r-rprotobuf@0.4.25 r-jsonlite@2.0.0 r-httr@1.4.7 r-data-table@1.17.8
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/traveltime-dev/traveltime-sdk-r
Licenses: Expat
Build system: r
Synopsis: Interface to 'Travel Time' API
Description:

Travel Time API <https://docs.traveltime.com/api/overview/introduction> helps users find locations by journey time rather than using â as the crow fliesâ distance. Time-based searching gives users more opportunities for personalisation and delivers a more relevant search.

r-torchvision 0.8.0
Propagated dependencies: r-zeallot@0.2.0 r-withr@3.0.2 r-torch@0.16.3 r-tiff@0.1-12 r-rlang@1.1.6 r-rappdirs@0.3.3 r-png@0.1-8 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-jpeg@0.1-11 r-glue@1.8.0 r-fs@1.6.6 r-cli@3.6.5 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://torchvision.mlverse.org
Licenses: Expat
Build system: r
Synopsis: Models, Datasets and Transformations for Images
Description:

This package provides access to datasets, models and preprocessing facilities for deep learning with images. Integrates seamlessly with the torch package and it's API borrows heavily from PyTorch vision package.

r-tidyrss 2.0.7
Propagated dependencies: r-xml2@1.5.0 r-vctrs@0.6.5 r-tidyselect@1.2.1 r-tibble@3.3.0 r-rlang@1.1.6 r-purrr@1.2.0 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-httr@1.4.7 r-glue@1.8.0 r-dplyr@1.1.4 r-anytime@0.3.12
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/RobertMyles/tidyrss
Licenses: Expat
Build system: r
Synopsis: Tidy RSS for R
Description:

With the objective of including data from RSS feeds into your analysis, tidyRSS parses RSS, Atom and JSON feeds and returns a tidy data frame.

r-tdarec 0.2.0
Propagated dependencies: r-vctrs@0.6.5 r-tidyr@1.3.1 r-tibble@3.3.0 r-scales@1.4.0 r-rlang@1.1.6 r-recipes@1.3.1 r-purrr@1.2.0 r-magrittr@2.0.4 r-dials@1.4.2
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/tdaverse/tdarec
Licenses: GPL 3+
Build system: r
Synopsis: 'recipes' Extension for Persistent Homology and Its Vectorizations
Description:

Topological data analytic methods in machine learning rely on vectorizations of the persistence diagrams that encode persistent homology, as surveyed by Ali &al (2000) <doi:10.48550/arXiv.2212.09703>. Persistent homology can be computed using TDA and ripserr and vectorized using TDAvec'. The Tidymodels package collection modularizes machine learning in R for straightforward extensibility; see Kuhn & Silge (2022, ISBN:978-1-4920-9644-3). These recipe steps and dials tuners make efficient algorithms for computing and vectorizing persistence diagrams available for Tidymodels workflows.

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