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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-tstests 1.0.1
Propagated dependencies: r-xts@0.14.1 r-tsmethods@1.0.3 r-rdpack@2.6.4 r-ks@1.15.1 r-flextable@0.9.10 r-data-table@1.17.8 r-car@3.1-3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://www.nopredict.com/packages/tstests
Licenses: GPL 2
Build system: r
Synopsis: Time Series Goodness of Fit and Forecast Evaluation Tests
Description:

Goodness of Fit and Forecast Evaluation Tests for timeseries models. Includes, among others, the Generalized Method of Moments (GMM) Orthogonality Test of Hansen (1982), the Nyblom (1989) parameter constancy test, the sign-bias test of Engle and Ng (1993), and a range of tests for value at risk and expected shortfall evaluation.

r-topksignal 1.0
Propagated dependencies: r-reshape2@1.4.5 r-nloptr@2.2.1 r-matrix@1.7-4 r-ggplot2@4.0.1 r-foreach@1.5.2 r-doparallel@1.0.17
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=TopKSignal
Licenses: GPL 2
Build system: r
Synopsis: Convex Optimization Tool for Signal Reconstruction from Multiple Ranked Lists
Description:

This package provides a mathematical optimization procedure in combination with statistical bootstrap for the estimation of the latent signals (sometimes called scores) informing the global consensus ranking (often named aggregation ranking). To solve mid/large-scale problems, users should install the gurobi optimiser (available from <https://www.gurobi.com/>).

r-topics 0.70
Dependencies: python@3.11.14
Propagated dependencies: r-tidyr@1.3.1 r-tibble@3.3.0 r-textminer@3.0.6 r-stringr@1.6.0 r-stringi@1.8.7 r-stopwords@2.3 r-rlang@1.1.6 r-readr@2.1.6 r-quanteda@4.3.1 r-purrr@1.2.0 r-patchwork@1.3.2 r-matrix@1.7-4 r-ggwordcloud@0.6.2 r-ggplot2@4.0.1 r-ggforce@0.5.0 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://r-topics.org/
Licenses: GPL 3
Build system: r
Synopsis: Creating and Significance Testing Language Features for Visualisation
Description:

This package implements differential language analysis with statistical tests and offers various language visualization techniques for n-grams and topics. It also supports the text package. For more information, visit <https://r-topics.org/> and <https://www.r-text.org/>.

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-tmapverse 0.1.0
Propagated dependencies: r-tmap-networks@0.1 r-tmap-mapgl@0.1.0 r-tmap-glyphs@0.1 r-tmap-cartogram@0.2 r-tmap@4.2 r-terra@1.8-86 r-stars@0.6-8 r-sf@1.0-23 r-crayon@1.5.3 r-cols4all@0.10 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=tmapverse
Licenses: GPL 3
Build system: r
Synopsis: Meta-Package for Thematic Mapping with 'tmap'
Description:

Attaches a set of packages commonly used for spatial plotting with tmap'. It includes tmap and its extensions ('tmap.glyphs', tmap.networks', tmap.cartogram', tmap.mapgl'), as well as supporting spatial data packages ('sf', stars', terra') and cols4all for exploring color palettes. The collection is designed for thematic mapping workflows and does not include the full set of packages from the R-spatial ecosystem.

r-tsvc 1.7.2
Propagated dependencies: r-vgam@1.1-13 r-tibble@3.3.0 r-plotrix@3.8-13 r-mgcv@1.9-4
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=TSVC
Licenses: GPL 2
Build system: r
Synopsis: Tree-Structured Modelling of Varying Coefficients
Description:

Fitting tree-structured varying coefficient models (Berger et al. (2019), <doi:10.1007/s11222-018-9804-8>). Simultaneous detection of covariates with varying coefficients and effect modifiers that induce varying coefficients if they are present.

r-tsibbledata 0.4.1
Propagated dependencies: r-vctrs@0.6.5 r-tsibble@1.2.0 r-rappdirs@0.3.3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://tsibbledata.tidyverts.org/
Licenses: GPL 3
Build system: r
Synopsis: Diverse Datasets for 'tsibble'
Description:

This package provides diverse datasets in the tsibble data structure. These datasets are useful for learning and demonstrating how tidy temporal data can tidied, visualised, and forecasted.

r-trnslate 0.0.3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: <https://marioma.me?i=soft>
Licenses: GPL 2+
Build system: r
Synopsis: Translate R Code in Source Files
Description:

Evaluate inline or chunks of R code in template files and replace with their output modifying the resulting template.

r-tsdisagg2 0.1.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tsdisagg2
Licenses: GPL 2+
Build system: r
Synopsis: Time Series Disaggregation
Description:

Disaggregates low frequency time series data to higher frequency series. Implements the following methods for temporal disaggregation: Boot, Feibes and Lisman (1967) <DOI:10.2307/2985238>, Chow and Lin (1971) <DOI:10.2307/1928739>, Fernandez (1981) <DOI:10.2307/1924371> and Litterman (1983) <DOI:10.2307/1391858>.

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-terrainr 0.7.6
Propagated dependencies: r-units@1.0-0 r-unifir@0.2.4 r-terra@1.8-86 r-sf@1.0-23 r-rlang@1.1.6 r-png@0.1-8 r-magick@2.9.0 r-httr@1.4.7 r-glue@1.8.0 r-ggplot2@4.0.1 r-base64enc@0.1-3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://docs.ropensci.org/terrainr/
Licenses: Expat
Build system: r
Synopsis: Landscape Visualizations in R and 'Unity'
Description:

This package provides functions for the retrieval, manipulation, and visualization of geospatial data, with an aim towards producing 3D landscape visualizations in the Unity 3D rendering engine. Functions are also provided for retrieving elevation data and base map tiles from the USGS National Map <https://apps.nationalmap.gov/services/>.

r-tbox 0.2.2
Propagated dependencies: r-rmarkdown@2.30 r-knitr@1.50 r-clipr@0.8.0 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/TanguyBarthelemy/TBox
Licenses: Expat
Build system: r
Synopsis: Useful Functions for Programming and Generating Documents
Description:

This package provides tools to help developers and producers manipulate R objects and outputs. It includes tools for displaying results and objects, and for formatting them in the correct format.

r-tinyscholar 0.1.7
Propagated dependencies: r-xml2@1.5.0 r-stringr@1.6.0 r-rvest@1.0.5 r-rlang@1.1.6 r-r-utils@2.13.0 r-purrr@1.2.0 r-magrittr@2.0.4 r-jsonlite@2.0.0 r-gt@1.3.0 r-ggplot2@4.0.1 r-dplyr@1.1.4 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/ShixiangWang/tinyscholar
Licenses: Expat
Build system: r
Synopsis: Get and Show Personal 'Google Scholar' Profile
Description:

This package provides functions to get personal Google Scholar profile data from web API and show it in table or figure format.

r-tablematrix 0.82.0
Propagated dependencies: 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=tableMatrix
Licenses: GPL 2
Build system: r
Synopsis: Combines 'data.table' and 'matrix' Classes
Description:

This package provides two classes extending data.table class. Simple tableList class wraps data.table and any additional structures together. More complex tableMatrix class combines data.table and matrix'. See <http://github.com/InferenceTechnologies/tableMatrix> for more information and examples.

r-textreg 0.1.5
Propagated dependencies: r-tm@0.7-16 r-rcpp@1.1.0 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=textreg
Licenses: Expat
Build system: r
Synopsis: n-Gram Text Regression, aka Concise Comparative Summarization
Description:

Function for sparse regression on raw text, regressing a labeling vector onto a feature space consisting of all possible phrases.

r-transplantr 0.2.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://transplantr.txtools.net
Licenses: GPL 3
Build system: r
Synopsis: Audit and Research Functions for Transplantation
Description:

This package provides a set of vectorised functions to calculate medical equations used in transplantation, focused mainly on transplantation of abdominal organs. These functions include donor and recipient risk indices as used by NHS Blood & Transplant, OPTN/UNOS and Eurotransplant, tools for quantifying HLA mismatches, functions for calculating estimated glomerular filtration rate (eGFR), a function to calculate the APRI (AST to platelet ratio) score used in initial screening of suitability to receive a transplant from a hepatitis C seropositive donor and some biochemical unit converter functions. All functions are designed to work with either US or international units. References for the equations are provided in the vignettes and function documentation.

r-tcrconvertr 1.0
Propagated dependencies: r-rappdirs@0.3.3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/seshadrilab/tcrconvertr
Licenses: Expat
Build system: r
Synopsis: Convert TCR Gene Names
Description:

Convert T Cell Receptor (TCR) gene names between the 10X Genomics, Adaptive Biotechnologies, and ImMunoGeneTics (IMGT) nomenclatures.

r-teal 1.1.0
Propagated dependencies: r-teal-widgets@0.6.0 r-teal-slice@0.7.1 r-teal-reporter@0.6.1 r-teal-logger@0.4.1 r-teal-data@0.8.0 r-teal-code@0.7.1 r-shinyjs@2.1.0 r-shiny@1.11.1 r-rlang@1.1.6 r-logger@0.4.1 r-lifecycle@1.0.4 r-jsonlite@2.0.0 r-htmltools@0.5.8.1 r-cli@3.6.5 r-checkmate@2.3.3 r-bslib@0.9.0 r-bsicons@0.1.2
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://insightsengineering.github.io/teal/
Licenses: ASL 2.0
Build system: r
Synopsis: Exploratory Web Apps for Analyzing Clinical Trials Data
Description:

This package provides a shiny based interactive exploration framework for analyzing clinical trials data. teal currently provides a dynamic filtering facility and different data viewers. teal shiny applications are built using standard shiny modules.

r-tempted 0.1.1
Propagated dependencies: r-np@0.60-18 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/pixushi/tempted
Licenses: GPL 3
Build system: r
Synopsis: Temporal Tensor Decomposition, a Dimensionality Reduction Tool for Longitudinal Multivariate Data
Description:

TEMPoral TEnsor Decomposition (TEMPTED), is a dimension reduction method for multivariate longitudinal data with varying temporal sampling. It formats the data into a temporal tensor and decomposes it into a summation of low-dimensional components, each consisting of a subject loading vector, a feature loading vector, and a continuous temporal loading function. These loadings provide a low-dimensional representation of subjects or samples and can be used to identify features associated with clusters of subjects or samples. TEMPTED provides the flexibility of allowing subjects to have different temporal sampling, so time points do not need to be binned, and missing time points do not need to be imputed.

r-transformerforecasting 0.1.0
Propagated dependencies: r-tensorflow@2.20.0 r-reticulate@1.44.1 r-magrittr@2.0.4 r-keras@2.16.1 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=transformerForecasting
Licenses: GPL 3
Build system: r
Synopsis: Transformer Deep Learning Model for Time Series Forecasting
Description:

Time series forecasting faces challenges due to the non-stationarity, nonlinearity, and chaotic nature of the data. Traditional deep learning models like Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) process data sequentially but are inefficient for long sequences. To overcome the limitations of these models, we proposed a transformer-based deep learning architecture utilizing an attention mechanism for parallel processing, enhancing prediction accuracy and efficiency. This paper presents user-friendly code for the implementation of the proposed transformer-based deep learning architecture utilizing an attention mechanism for parallel processing. References: Nayak et al. (2024) <doi:10.1007/s40808-023-01944-7> and Nayak et al. (2024) <doi:10.1016/j.simpa.2024.100716>.

r-table-express 0.4.2
Propagated dependencies: r-tidyselect@1.2.1 r-rlang@1.1.6 r-r6@2.6.1 r-magrittr@2.0.4 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://asardaes.github.io/table.express/
Licenses: FSDG-compatible
Build system: r
Synopsis: Build 'data.table' Expressions with Data Manipulation Verbs
Description:

This package provides a specialization of dplyr data manipulation verbs that parse and build expressions which are ultimately evaluated by data.table', letting it handle all optimizations. A set of additional verbs is also provided to facilitate some common operations on a subset of the data.

r-tpwb 0.1.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tpwb
Licenses: GPL 3
Build system: r
Synopsis: The Three Parameter Weibull Distribution
Description:

Density, distribution function, the quantile function, random generation function, and maximum likelihood estimation.

r-theft 0.8.2
Propagated dependencies: r-tsibble@1.2.0 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@0.5.0 r-fabletools@0.6.1 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-tteice 1.1.3
Propagated dependencies: r-survival@3.8-3 r-shinywidgets@0.9.0 r-shinythemes@1.2.0 r-shiny@1.11.1 r-psych@2.5.6 r-mass@7.3-65 r-lifecycle@1.0.4 r-dt@0.34.0 r-cmprsk@2.2-12
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/mephas/tteICE
Licenses: GPL 3
Build system: r
Synopsis: Treatment Effect Estimation for Time-to-Event Data with Intercurrent Events
Description:

Analysis of treatment effects in clinical trials with time-to-event outcomes is complicated by intercurrent events. This package implements methods for estimating and inferring the cumulative incidence functions for time-to-event (TTE) outcomes with intercurrent events (ICE) under the five strategies outlined in the ICH E9 (R1) addendum, see Deng (2025) <doi:10.1002/sim.70091>. This package can be used for analyzing data from both randomized controlled trials and observational studies. In general, the data involve a primary outcome event and, potentially, an intercurrent event. Two data structures are allowed: competing risks, where only the time to the first event is recorded, and semicompeting risks, where the times to both the primary outcome event and intercurrent event (or censoring) are recorded. For estimation methods, users can choose nonparametric estimation (which does not use covariates) and semiparametrically efficient estimation.

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