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

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-tensorpreave 1.1.0
Propagated dependencies: r-rtensor@1.4.9 r-pracma@2.4.6 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/William-Chenwl/TensorPreAve
Licenses: GPL 3
Build system: r
Synopsis: Rank and Factor Loadings Estimation in Time Series Tensor Factor Models
Description:

This package provides a set of functions to estimate rank and factor loadings of time series tensor factor models. A tensor is a multidimensional array. To analyze high-dimensional tensor time series, factor model is a major dimension reduction tool. TensorPreAve provides functions to estimate the rank of core tensors and factor loading spaces of tensor time series. More specifically, a pre-averaging method that accumulates information from tensor fibres is used to estimate the factor loading spaces. The estimated directions corresponding to the strongest factors are then used for projecting the data for a potentially improved re-estimation of the factor loading spaces themselves. A new rank estimation method is also implemented to utilizes correlation information from the projected data. See Chen and Lam (2023) <arXiv:2208.04012> for more details.

r-tres 1.1.5
Propagated dependencies: r-rtensor@1.4.9 r-pracma@2.4.6 r-mass@7.3-65 r-manifoldoptim@1.0.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/leozeng15/TRES
Licenses: GPL 3
Build system: r
Synopsis: Tensor Regression with Envelope Structure
Description:

This package provides three estimators for tensor response regression (TRR) and tensor predictor regression (TPR) models with tensor envelope structure. The three types of estimation approaches are generic and can be applied to any envelope estimation problems. The full Grassmannian (FG) optimization is often associated with likelihood-based estimation but requires heavy computation and good initialization; the one-directional optimization approaches (1D and ECD algorithms) are faster, stable and does not require carefully chosen initial values; the SIMPLS-type is motivated by the partial least squares regression and is computationally the least expensive. For details of TRR, see Li L, Zhang X (2017) <doi:10.1080/01621459.2016.1193022>. For details of TPR, see Zhang X, Li L (2017) <doi:10.1080/00401706.2016.1272495>. For details of 1D algorithm, see Cook RD, Zhang X (2016) <doi:10.1080/10618600.2015.1029577>. For details of ECD algorithm, see Cook RD, Zhang X (2018) <doi:10.5705/ss.202016.0037>. For more details of the package, see Zeng J, Wang W, Zhang X (2021) <doi:10.18637/jss.v099.i12>.

r-td 0.0.6
Propagated dependencies: r-rcppsimdjson@0.1.15
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://dirk.eddelbuettel.com/code/td.html
Licenses: GPL 2+
Build system: r
Synopsis: Access to the 'twelvedata' Financial Data API
Description:

The twelvedata REST service offers access to current and historical data on stocks, standard as well as digital crypto currencies, and other financial assets covering a wide variety of course and time spans. See <https://twelvedata.com/> for details, to create an account, and to request an API key for free-but-capped access to the data.

r-tidyseurat 0.8.10
Propagated dependencies: r-vctrs@0.6.5 r-ttservice@0.5.3 r-tidyselect@1.2.1 r-tidyr@1.3.1 r-tibble@3.3.0 r-stringr@1.6.0 r-seuratobject@5.2.0 r-seurat@5.3.1 r-rlang@1.1.6 r-purrr@1.2.0 r-plotly@4.11.0 r-pillar@1.11.1 r-matrix@1.7-4 r-magrittr@2.0.4 r-lifecycle@1.0.4 r-ggplot2@4.0.1 r-generics@0.1.4 r-fansi@1.0.7 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/stemangiola/tidyseurat
Licenses: GPL 3
Build system: r
Synopsis: Brings Seurat to the Tidyverse
Description:

It creates an invisible layer that allow to see the Seurat object as tibble and interact seamlessly with the tidyverse.

r-timechecker 1.1.5
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=timechecker
Licenses: GPL 3
Build system: r
Synopsis: Visualization of Processing Time with Standard Output
Description:

Displays processing time in a clear and structured way. One function supports iterative workflows by predicting and showing the total time required, while another reports the time taken for individual steps within a process.

r-topicdoc 0.1.1
Propagated dependencies: r-topicmodels@0.2-17 r-slam@0.1-55
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/doug-friedman/topicdoc
Licenses: Expat
Build system: r
Synopsis: Topic-Specific Diagnostics for LDA and CTM Topic Models
Description:

Calculates topic-specific diagnostics (e.g. mean token length, exclusivity) for Latent Dirichlet Allocation and Correlated Topic Models fit using the topicmodels package. For more details, see Chapter 12 in Airoldi et al. (2014, ISBN:9781466504080), pp 262-272 Mimno et al. (2011, ISBN:9781937284114), and Bischof et al. (2014) <arXiv:1206.4631v1>.

r-tanaka 0.4.0
Propagated dependencies: r-terra@1.8-86 r-sf@1.0-23 r-maplegend@0.5.0 r-mapiso@0.3.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/riatelab/tanaka/
Licenses: GPL 3
Build system: r
Synopsis: Design Shaded Contour Lines (or Tanaka) Maps
Description:

The Tanaka method enhances the representation of topography on a map using shaded contour lines. In this simplified implementation of the method, north-west white contours represent illuminated topography and south-east black contours represent shaded topography. See Tanaka (1950) <doi:10.2307/211219>.

r-timedelay 1.0.11
Propagated dependencies: r-mvtnorm@1.3-3 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=timedelay
Licenses: GPL 2
Build system: r
Synopsis: Time Delay Estimation for Stochastic Time Series of Gravitationally Lensed Quasars
Description:

We provide a toolbox to estimate the time delay between the brightness time series of gravitationally lensed quasar images via Bayesian and profile likelihood approaches. The model is based on a state-space representation for irregularly observed time series data generated from a latent continuous-time Ornstein-Uhlenbeck process. Our Bayesian method adopts scientifically motivated hyper-prior distributions and a Metropolis-Hastings within Gibbs sampler, producing posterior samples of the model parameters that include the time delay. A profile likelihood of the time delay is a simple approximation to the marginal posterior distribution of the time delay. Both Bayesian and profile likelihood approaches complement each other, producing almost identical results; the Bayesian way is more principled but the profile likelihood is easier to implement. A new functionality is added in version 1.0.9 for estimating the time delay between doubly-lensed light curves observed in two bands. See also Tak et al. (2017) <doi:10.1214/17-AOAS1027>, Tak et al. (2018) <doi:10.1080/10618600.2017.1415911>, Hu and Tak (2020) <arXiv:2005.08049>.

r-temper 1.1.0
Propagated dependencies: r-torch@0.16.3 r-scales@1.4.0 r-purrr@1.2.0 r-lubridate@1.9.4 r-imputets@3.4 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://rpubs.com/giancarlo_vercellino/temper
Licenses: GPL 3
Build system: r
Synopsis: Temporal Encoder-Masked Probabilistic Ensemble Regressor
Description:

This package implements a probabilistic ensemble time-series forecaster that combines an auto-encoder with a neural decision forest whose split variables are learned through a differentiable feature-mask layer. Functions are written with torch tensors and provide CRPS (Continuous Ranked Probability Scores) training plus mixture-distribution post-processing.

r-toolmark 0.0.1
Propagated dependencies: r-reshape2@1.4.5 r-plyr@1.8.9 r-ggplot2@4.0.1 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=toolmaRk
Licenses: GPL 3
Build system: r
Synopsis: Tests for Same-Source of Toolmarks
Description:

This package implements two tests for same-source of toolmarks. The chumbley_non_random() test follows the paper "An Improved Version of a Tool Mark Comparison Algorithm" by Hadler and Morris (2017) <doi:10.1111/1556-4029.13640>. This is an extension of the Chumbley score as previously described in "Validation of Tool Mark Comparisons Obtained Using a Quantitative, Comparative, Statistical Algorithm" by Chumbley et al (2010) <doi:10.1111/j.1556-4029.2010.01424.x>. fixed_width_no_modeling() is based on correlation measures in a diamond shaped area of the toolmark as described in Hadler (2017).

r-trekcolors 0.2.0
Propagated dependencies: r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/leonawicz/trekcolors
Licenses: Expat
Build system: r
Synopsis: Star Trek Color Palettes
Description:

This package provides a dataset of predefined color palettes based on the Star Trek science fiction series, associated color palette functions, and additional functions for generating customized palettes that are on theme. The package also offers functions for applying the palettes to plots made using the ggplot2 package.

r-tidycwl 1.0.7
Propagated dependencies: r-yaml@2.3.10 r-webshot@0.5.5 r-visnetwork@2.1.4 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-htmlwidgets@1.6.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://sbg.github.io/tidycwl/
Licenses: AGPL 3
Build system: r
Synopsis: Tidy Common Workflow Language Tools and Workflows
Description:

The Common Workflow Language <https://www.commonwl.org/> is an open standard for describing data analysis workflows. This package takes the raw Common Workflow Language workflows encoded in JSON or YAML and turns the workflow elements into tidy data frames or lists. A graph representation for the workflow can be constructed and visualized with the parsed workflow inputs, outputs, and steps. Users can embed the visualizations in their Shiny applications, and export them as HTML files or static images.

r-tsapp 1.0.4
Propagated dependencies: r-vars@1.6-1 r-matrix@1.7-4 r-hdm@0.3.2 r-fftwtools@0.9-11
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tsapp
Licenses: GPL 2+ GPL 3+
Build system: r
Synopsis: Time Series, Analysis and Application
Description:

Accompanies the book Rainer Schlittgen and Cristina Sattarhoff (2020) <https://www.degruyter.com/view/title/575978> "Angewandte Zeitreihenanalyse mit R, 4. Auflage" . The package contains the time series and functions used therein. It was developed over many years teaching courses about time series analysis.

r-tm-plugin-mail 0.3-1
Propagated dependencies: r-tm@0.7-16 r-reticulate@1.44.1 r-nlp@0.3-2
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tm.plugin.mail
Licenses: GPL 3
Build system: r
Synopsis: Text Mining E-Mail Plug-in
Description:

This package provides a plug-in for the tm text mining framework providing mail handling functionality.

r-tideharmonics 0.1-1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=TideHarmonics
Licenses: Modified BSD
Build system: r
Synopsis: Harmonic Analysis of Tides
Description:

This package implements harmonic analysis of tidal and sea-level data. Over 400 harmonic tidal constituents can be estimated, all with daily nodal corrections. Time-varying mean sea-levels can also be used.

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-testcomparer 1.1.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://kajlinko.github.io/testCompareR/
Licenses: GPL 3
Build system: r
Synopsis: Comparing Two Diagnostic Tests with Dichotomous Results using Paired Data
Description:

This package provides a method for comparing the results of two binary diagnostic tests using paired data. Users can rapidly perform descriptive and inferential statistics in a single function call. Options permit users to select which parameters they are interested in comparing and methods for correction for multiple comparisons. Confidence intervals are calculated using the methods with the best coverage. Hypothesis tests use the methods with the best asymptotic performance. A summary of the methods is available in Roldán-Nofuentes (2020) <doi:10.1186/s12874-020-00988-y>. This package is targeted at clinical researchers who want to rapidly and effectively compare results from binary diagnostic tests.

r-tfre 0.1.0
Propagated dependencies: r-rcppparallel@5.1.11-1 r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=TFRE
Licenses: GPL 2+
Build system: r
Synopsis: Tuning-Free Robust and Efficient Approach to High-Dimensional Regression
Description:

Provide functions to estimate the coefficients in high-dimensional linear regressions via a tuning-free and robust approach. The method was published in Wang, L., Peng, B., Bradic, J., Li, R. and Wu, Y. (2020), "A Tuning-free Robust and Efficient Approach to High-dimensional Regression", Journal of the American Statistical Association, 115:532, 1700-1714(JASAâ s discussion paper), <doi:10.1080/01621459.2020.1840989>. See also Wang, L., Peng, B., Bradic, J., Li, R. and Wu, Y. (2020), "Rejoinder to â A tuning-free robust and efficient approach to high-dimensional regression". Journal of the American Statistical Association, 115, 1726-1729, <doi:10.1080/01621459.2020.1843865>; Peng, B. and Wang, L. (2015), "An Iterative Coordinate Descent Algorithm for High-Dimensional Nonconvex Penalized Quantile Regression", Journal of Computational and Graphical Statistics, 24:3, 676-694, <doi:10.1080/10618600.2014.913516>; Clémençon, S., Colin, I., and Bellet, A. (2016), "Scaling-up empirical risk minimization: optimization of incomplete u-statistics", The Journal of Machine Learning Research, 17(1):2682â 2717; Fan, J. and Li, R. (2001), "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties", Journal of the American Statistical Association, 96:456, 1348-1360, <doi:10.1198/016214501753382273>.

r-taskqueue 0.2.0
Propagated dependencies: r-whisker@0.4.1 r-stringr@1.6.0 r-ssh@0.9.4 r-shiny@1.11.1 r-settings@0.2.7 r-rpostgres@1.4.8 r-rlang@1.1.6 r-ggplot2@4.0.1 r-dbi@1.2.3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://taskqueue.bangyou.me/
Licenses: Expat
Build system: r
Synopsis: Task Queue for Parallel Computing Based on PostgreSQL
Description:

This package implements a task queue system for asynchronous parallel computing using PostgreSQL <https://www.postgresql.org/> as a backend. Designed for embarrassingly parallel problems where tasks do not communicate with each other. Dynamically distributes tasks to workers, handles uneven load balancing, and allows new workers to join at any time. Particularly useful for running large numbers of independent tasks on high-performance computing (HPC) clusters with SLURM <https://slurm.schedmd.com/> job schedulers.

r-tidyedsurvey 0.1.4
Propagated dependencies: r-tidyselect@1.2.1 r-rlang@1.1.6 r-lifecycle@1.0.4 r-ggplot2@4.0.1 r-edsurvey@4.0.7 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://cran.r-project.org/package=tidyEdSurvey
Licenses: GPL 2
Build system: r
Synopsis: Integration of 'dplyr' and 'ggplot2' with 'EdSurvey'
Description:

Takes objects of class edsurvey.data.frame and converts them to a data.frame within the calling environment of dplyr and ggplot2 functions. Additionally, for plotting with ggplot2', users can map aesthetics to subject scales and all plausible values will be used. This package supports student level data; to work with school or teacher level data, see ?EdSurvey::getData'.

r-testthatdocs 1.0.23
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/urniaz/testthatdocs
Licenses: Expat
Build system: r
Synopsis: Automated and Idempotent Unit Tests Documentation for Reproducible Quality Assurance
Description:

Automates documentation of test_that() calls within R test files. The package scans test sources, extracts human-readable test titles (even when composed with functions like paste() or glue::glue(), ... etc.), and generates reproducible roxygen2-style listings that can be inserted both globally and per-section. It ensures idempotent updates and supports customizable numbering templates with hierarchical indices. Designed for developers, QA teams, and package maintainers seeking consistent, self-documenting test inventories.

r-temporalforest 0.1.4
Propagated dependencies: r-wgcna@1.73 r-partykit@1.2-24 r-glmertree@0.2-6 r-flashclust@1.01-2 r-dynamictreecut@1.63-1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/SisiShao/TemporalForest
Licenses: Expat
Build system: r
Synopsis: Network-Guided Temporal Forests for Feature Selection in High-Dimensional Longitudinal Data
Description:

This package implements the Temporal Forest algorithm for feature selection in high-dimensional longitudinal data. The method combines time-aware network construction via weighted gene co-expression network analysis (WGCNA), module-based feature screening, and stability selection using tree-based models. This package provides tools for reproducible longitudinal analysis, closely following the methodology described in Shao, Moore, and Ramirez (2025) <https://github.com/SisiShao/TemporalForest>.

r-timer 1.2.0
Propagated dependencies: r-r6@2.6.1 r-lubridate@1.9.4
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/yusuzech/timeR
Licenses: ASL 2.0 FSDG-compatible
Build system: r
Synopsis: Time Your Codes
Description:

This package provides a timeR class that makes timing codes easier. One can create timeR objects and use them to record all timings, and extract recordings as data frame for later use.

r-tmvmixnorm 1.1.1
Propagated dependencies: r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tmvmixnorm
Licenses: GPL 2
Build system: r
Synopsis: Sampling from Truncated Multivariate Normal and t Distributions
Description:

Efficient sampling of truncated multivariate (scale) mixtures of normals under linear inequality constraints is nontrivial due to the analytically intractable normalizing constant. Meanwhile, traditional methods may subject to numerical issues, especially when the dimension is high and dependence is strong. Algorithms proposed by Li and Ghosh (2015) <doi: 10.1080/15598608.2014.996690> are adopted for overcoming difficulties in simulating truncated distributions. Efficient rejection sampling for simulating truncated univariate normal distribution is included in the package, which shows superiority in terms of acceptance rate and numerical stability compared to existing methods and R packages. An efficient function for sampling from truncated multivariate normal distribution subject to convex polytope restriction regions based on Gibbs sampler for conditional truncated univariate distribution is provided. By extending the sampling method, a function for sampling truncated multivariate Student's t distribution is also developed. Moreover, the proposed method and computation remain valid for high dimensional and strong dependence scenarios. Empirical results in Li and Ghosh (2015) <doi: 10.1080/15598608.2014.996690> illustrated the superior performance in terms of various criteria (e.g. mixing and integrated auto-correlation time).

Page: 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372373374375376377378379380381382383384385386387388389390391392393394395396397398399400401402403404405406407408409410411412413414415416417418419420421422423424425426427428429430431432433434435436437438439440441442443444445446447448449450451452453454455456457458459460461462463464465466467468469470471472473474475476477478479480481482483484485486487488489490491492493494495496497498499500501502503504505506507508509510511512513514515516517518519520521522523524525526527528529530531532533534535536537538539540541542543544545546547548549550551552553554555556557558559560561562563564565566567568569570571572573574575576577578579580581582583584585586587588589590591592593594595596597598599600601602603604605606607608609610611612613614615616617618619620621622623624625626627628629630631632633634635636637638639640641642643644645646647648649650651652653654655656657658659660661662663664665666667668669670671672673674675676677678679680681682683684685686687688689690691692693694695696697698699700701702703704705706707708709710711712713714715716717718719720721722723724725726727728729730731732733734735736737738739740741742743744745746747748749750751752753754755756757758759760761762763764765766767768769770771772773774775776777778779780781782783784785786787788789790791792793794795796797798799800801802803804805806807808809810811812813814815816817818819820821822823824825826827828829830831832833834835836837838839840841842843844845846847848849850851852853854855856857858859860861862863864865866867868869870871872873874875876877878879880881882883884885886887888889890891892893894895
Total results: 21457