_            _    _        _         _
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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-tipmap 0.5.2
Propagated dependencies: r-rbest@1.8-2 r-purrr@1.2.0 r-magrittr@2.0.4 r-ggplot2@4.0.1 r-future@1.68.0 r-furrr@0.3.1 r-dplyr@1.1.4 r-assertthat@0.2.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/Boehringer-Ingelheim/tipmap
Licenses: ASL 2.0
Build system: r
Synopsis: Tipping Point Analysis for Bayesian Dynamic Borrowing
Description:

Tipping point analysis for clinical trials that employ Bayesian dynamic borrowing via robust meta-analytic predictive (MAP) priors. Further functions facilitate expert elicitation of a primary weight of the informative component of the robust MAP prior and computation of operating characteristics. Intended use is the planning, analysis and interpretation of extrapolation studies in pediatric drug development, but applicability is generally wider.

r-treatmentpatterns 3.1.2
Propagated dependencies: r-tidyr@1.3.1 r-stringi@1.8.7 r-r6@2.6.1 r-jsonlite@2.0.0 r-dplyr@1.1.4 r-dbplyr@2.5.1 r-checkmate@2.3.3 r-cdmconnector@2.3.0 r-andromeda@1.2.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/darwin-eu/TreatmentPatterns
Licenses: FSDG-compatible
Build system: r
Synopsis: Analyzes Real-World Treatment Patterns of a Study Population of Interest
Description:

Computes treatment patterns within a given cohort using the Observational Medical Outcomes Partnership (OMOP) common data model (CDM). As described in Markus, Verhamme, Kors, and Rijnbeek (2022) <doi:10.1016/j.cmpb.2022.107081>.

r-tushare 0.1.4
Propagated dependencies: r-tidyverse@2.0.0 r-httr@1.4.7 r-forecast@8.24.0 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=Tushare
Licenses: GPL 2
Build system: r
Synopsis: Interface to 'Tushare Pro' API
Description:

Helps the R users to get data from Tushare Pro'<https://tushare.pro>. Tushare Pro is a platform as well as a community with a lot of staffs working in financial area. We support financial data such as stock price, financial report statements and digital coins data.

r-transurv 1.2.4
Propagated dependencies: r-truncsp@1.2.4 r-survival@3.8-3 r-squarem@2021.1 r-rootsolve@1.8.2.4
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/stc04003/tranSurv
Licenses: GPL 3+
Build system: r
Synopsis: Transformation-Based Regression under Dependent Truncation
Description:

This package provides a latent, quasi-independent truncation time is assumed to be linked with the observed dependent truncation time, the event time, and an unknown transformation parameter via a structural transformation model. The transformation parameter is chosen to minimize the conditional Kendall's tau (Martin and Betensky, 2005) <doi:10.1198/016214504000001538> or the regression coefficient estimates (Jones and Crowley, 1992) <doi:10.2307/2336782>. The marginal distribution for the truncation time and the event time are completely left unspecified. The methodology is applied to survival curve estimation and regression analysis.

r-tetrascatt 0.1.1
Propagated dependencies: 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://cran.r-project.org/package=tetrascatt
Licenses: GPL 2+
Build system: r
Synopsis: Acoustic Scattering for Complex Shapes by Using the DWBA
Description:

Uses the Distorted Wave Born Approximation (DWBA) to compute the acoustic backward scattering, the geometry of the object is formed by a volumetric mesh, composed of tetrahedrons. This computation is done efficiently through an analytical 3D integration that allows for a solution which is expressed in terms of elementary functions for each tetrahedron. It is important to note that this method is only valid for objects whose acoustic properties, such as density and sound speed, do not vary significantly compared to the surrounding medium. (See Lavia, Cascallares and Gonzalez, J. D. (2023). TetraScatt model: Born approximation for the estimation of acoustic dispersion of fluid-like objects of arbitrary geometries. arXiv preprint <arXiv:2312.16721>).

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-thematic 0.1.8
Propagated dependencies: r-scales@1.4.0 r-rstudioapi@0.17.1 r-rlang@1.1.6 r-rappdirs@0.3.3 r-ggplot2@4.0.1 r-farver@2.1.2
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://rstudio.github.io/thematic/
Licenses: Expat
Build system: r
Synopsis: Unified and Automatic 'Theming' of 'ggplot2', 'lattice', and 'base' R Graphics
Description:

Theme ggplot2', lattice', and base graphics based on a few choices, including foreground color, background color, accent color, and font family. Fonts that aren't available on the system, but are available via download on Google Fonts', can be automatically downloaded, cached, and registered for use with the showtext and ragg packages.

r-toxdrc 1.0.1
Propagated dependencies: r-rlang@1.1.6 r-purrr@1.2.0 r-outliers@0.15 r-magrittr@2.0.4 r-drc@3.0-1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/jsalole/toxdrc
Licenses: Expat
Build system: r
Synopsis: Pipeline for Dose-Response Curve Analysis
Description:

This package provides a variety of tools for assessing dose response curves, with an emphasis on toxicity test data. The main feature of this package are modular functions which can be combined through the namesake pipeline, runtoxdrc', to automate the analysis for large and complex datasets. This includes optional data preprocessing steps, like outlier detection, solvent effects, blank correction, averaging technical replicates, and much more. Additionally, this pipeline is adaptable to any long form dataset, and does not require specific column or group naming to work.

r-teal-reporter 0.6.0
Propagated dependencies: r-zip@2.3.3 r-yaml@2.3.10 r-teal-data@0.8.0 r-teal-code@0.7.1 r-sortable@0.6.0 r-shinywidgets@0.9.0 r-shinyjs@2.1.0 r-shinybusy@0.3.3 r-shiny@1.11.1 r-rtables-officer@0.1.2 r-rtables@0.6.15 r-rmarkdown@2.30 r-rlistings@0.2.13 r-rlang@1.1.6 r-r6@2.6.1 r-lifecycle@1.0.4 r-knitr@1.50 r-jsonlite@2.0.0 r-htmltools@0.5.8.1 r-gtsummary@2.5.0 r-flextable@0.9.10 r-commonmark@2.0.0 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://github.com/insightsengineering/teal.reporter
Licenses: ASL 2.0
Build system: r
Synopsis: Reporting Tools for 'shiny' Modules
Description:

Prebuilt shiny modules containing tools for the generation of rmarkdown reports, supporting reproducible research and analysis.

r-traminerextras 0.6.8
Propagated dependencies: r-traminer@2.2-13 r-survival@3.8-3 r-rcolorbrewer@1.1-3 r-foreach@1.5.2 r-doparallel@1.0.17 r-colorspace@2.1-2 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: http://traminer.unige.ch/
Licenses: GPL 2+
Build system: r
Synopsis: TraMineR Extension
Description:

Collection of ancillary functions and utilities to be used in conjunction with the TraMineR package for sequence data exploration. Includes, among others, specific functions such as state survival plots, position-wise group-typical states, dynamic sequence indicators, and dissimilarities between event sequences. Also includes contributions by non-members of the TraMineR team such as methods for polyadic data and for the comparison of groups of sequences.

r-tipr 1.0.2
Propagated dependencies: r-tibble@3.3.0 r-sensemakr@0.1.6 r-rlang@1.1.6 r-purrr@1.2.0 r-glue@1.8.0 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://r-causal.github.io/tipr/
Licenses: Expat
Build system: r
Synopsis: Tipping Point Analyses
Description:

The strength of evidence provided by epidemiological and observational studies is inherently limited by the potential for unmeasured confounding. We focus on three key quantities: the observed bound of the confidence interval closest to the null, the relationship between an unmeasured confounder and the outcome, for example a plausible residual effect size for an unmeasured continuous or binary confounder, and the relationship between an unmeasured confounder and the exposure, for example a realistic mean difference or prevalence difference for this hypothetical confounder between exposure groups. Building on the methods put forth by Cornfield et al. (1959), Bross (1966), Schlesselman (1978), Rosenbaum & Rubin (1983), Lin et al. (1998), Lash et al. (2009), Rosenbaum (1986), Cinelli & Hazlett (2020), VanderWeele & Ding (2017), and Ding & VanderWeele (2016), we can use these quantities to assess how an unmeasured confounder may tip our result to insignificance.

r-tidynorm 0.4.0
Propagated dependencies: r-tidyselect@1.2.1 r-tidyr@1.3.1 r-stringr@1.6.0 r-rlang@1.1.6 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-purrr@1.2.0 r-options@0.3.1 r-glue@1.8.0 r-dplyr@1.1.4 r-cli@3.6.5 r-checkmate@2.3.3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://jofrhwld.github.io/tidynorm/
Licenses: GPL 3+
Build system: r
Synopsis: Tools for Tidy Vowel Normalization
Description:

An implementation of tidy speaker vowel normalization. This includes generic functions for defining new normalization methods for points, formant tracks, and Discrete Cosine Transform coefficients, as well as convenience functions implementing established normalization methods. References for the implemented methods are: Johnson, Keith (2020) <doi:10.5334/labphon.196> Lobanov, Boris (1971) <doi:10.1121/1.1912396> Nearey, Terrance M. (1978) <https://sites.ualberta.ca/~tnearey/Nearey1978_compressed.pdf> Syrdal, Ann K., and Gopal, H. S. (1986) <doi:10.1121/1.393381> Watt, Dominic, and Fabricius, Anne (2002) <https://www.latl.leeds.ac.uk/article/evaluation-of-a-technique-for-improving-the-mapping-of-multiple-speakers-vowel-spaces-in-the-f1-f2-plane/>.

r-triadsim 0.3.0
Propagated dependencies: r-snpstats@1.60.0 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=TriadSim
Licenses: GPL 3
Build system: r
Synopsis: Simulating Triad Genomewide Genotypes
Description:

Simulate genotypes for case-parent triads, case-control, and quantitative trait samples with realistic linkage diequilibrium structure and allele frequency distribution. For studies of epistasis one can simulate models that involve specific SNPs at specific sets of loci, which we will refer to as "pathways". TriadSim generates genotype data by resampling triad genotypes from existing data. The details of the method is described in the manuscript under preparation "Simulating Autosomal Genotypes with Realistic Linkage Disequilibrium and a Spiked in Genetic Effect" Shi, M., Umbach, D.M., Wise A.S., Weinberg, C.R.

r-trialemulation 0.0.4.9
Propagated dependencies: r-sandwich@3.1-1 r-rcpp@1.1.0 r-mvtnorm@1.3-3 r-lmtest@0.9-40 r-lifecycle@1.0.4 r-formula-tools@1.7.1 r-duckdb@1.4.2 r-dbi@1.2.3 r-data-table@1.17.8 r-checkmate@2.3.3 r-broom@1.0.10
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://causal-lda.github.io/TrialEmulation/
Licenses: FSDG-compatible
Build system: r
Synopsis: Causal Analysis of Observational Time-to-Event Data
Description:

This package implements target trial emulation methods to apply randomized clinical trial design and analysis in an observational setting. Using marginal structural models, it can estimate intention-to-treat and per-protocol effects in emulated trials using electronic health records. A description and application of the method can be found in Danaei et al (2013) <doi:10.1177/0962280211403603>.

r-traudem 1.0.3
Propagated dependencies: r-withr@3.0.2 r-sys@3.4.3 r-rlang@1.1.6 r-purrr@1.2.0 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://lucarraro.github.io/traudem/
Licenses: Expat
Build system: r
Synopsis: Use TauDEM
Description:

Simple trustworthy utility functions to use TauDEM (Terrain Analysis Using Digital Elevation Models <https://hydrology.usu.edu/taudem/taudem5/>) command-line interface. This package provides a guide to installation of TauDEM and its dependencies GDAL (Geopatial Data Abstraction Library) and MPI (Message Passing Interface) for different operating systems. Moreover, it checks that TauDEM and its dependencies are correctly installed and included to the PATH, and it provides wrapper commands for calling TauDEM methods from R.

r-tvmm 3.2.1
Propagated dependencies: r-tcltk2@1.6.1 r-robustbase@0.99-6 r-mass@7.3-65 r-gridextra@2.3 r-ggplot2@4.0.1 r-desctoolsaddins@1.12
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=TVMM
Licenses: GPL 2
Build system: r
Synopsis: Multivariate Tests for the Vector of Means
Description:

This is a statistical tool interactive that provides multivariate statistical tests that are more powerful than traditional Hotelling T2 test and LRT (likelihood ratio test) for the vector of normal mean populations with and without contamination and non-normal populations (Henrique J. P. Alves & Daniel F. Ferreira (2019) <DOI: 10.1080/03610918.2019.1693596>).

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-text-alignment 0.1.5
Propagated dependencies: r-rcpp@1.1.0
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/DIGI-VUB/text.alignment
Licenses: Expat
Build system: r
Synopsis: Text Alignment with Smith-Waterman
Description:

Find similarities between texts using the Smith-Waterman algorithm. The algorithm performs local sequence alignment and determines similar regions between two strings. The Smith-Waterman algorithm is explained in the paper: "Identification of common molecular subsequences" by T.F.Smith and M.S.Waterman (1981), available at <doi:10.1016/0022-2836(81)90087-5>. This package implements the same logic for sequences of words and letters instead of molecular sequences.

r-timp 1.13.6
Propagated dependencies: r-nnls@1.6 r-minpack-lm@1.2-4 r-gplots@3.2.0 r-gclus@1.3.3 r-fields@17.1 r-desolve@1.40 r-colorspace@2.1-2
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/glotaran/TIMP
Licenses: GPL 2+
Build system: r
Synopsis: Fitting Separable Nonlinear Models in Spectroscopy and Microscopy
Description:

This package provides a problem solving environment (PSE) for fitting separable nonlinear models to measurements arising in physics and chemistry experiments, as described by Mullen & van Stokkum (2007) <doi:10.18637/jss.v018.i03> for its use in fitting time resolved spectroscopy data, and as described by Laptenok et al. (2007) <doi:10.18637/jss.v018.i08> for its use in fitting Fluorescence Lifetime Imaging Microscopy (FLIM) data, in the study of Förster Resonance Energy Transfer (FRET). `TIMP` also serves as the computation backend for the `GloTarAn` software, a graphical user interface for the package, as described in Snellenburg et al. (2012) <doi:10.18637/jss.v049.i03>.

r-tinsel 0.0.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/nteetor/tinsel
Licenses: Expat
Build system: r
Synopsis: Transform Functions using Decorators
Description:

Instead of nesting function calls, annotate and transform functions using "#." comments.

r-tablaxlsx 1.2.6
Propagated dependencies: r-openxlsx@4.2.8.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tablaxlsx
Licenses: GPL 3
Build system: r
Synopsis: Write Formatted Tables in Excel Workbooks
Description:

For writing tables with custom formats in a Excel file ready to be distributed.

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).

r-twostepclogit 1.2.6
Propagated dependencies: r-survival@3.8-3
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=TwoStepCLogit
Licenses: GPL 2
Build system: r
Synopsis: Conditional Logistic Regression: A Two-Step Estimation Method
Description:

Conditional logistic regression with longitudinal follow up and individual-level random coefficients: A stable and efficient two-step estimation method.

r-tempr 0.10.1.1
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://cran.r-project.org/package=tempR
Licenses: GPL 2+
Build system: r
Synopsis: Temporal Sensory Data Analysis
Description:

Analysis and visualization of data from temporal sensory methods, including for temporal check-all-that-apply (TCATA) and temporal dominance of sensations (TDS). Methods are mainly from manuscripts by Castura, J.C., Antúnez, L., Giménez, A., and Ares, G. (2016) <doi:10.1016/j.foodqual.2015.06.017>, Castura, Baker, and Ross (2016) <doi:10.1016/j.foodqual.2016.06.011>, and Pineau et al. (2009) <doi:10.1016/j.foodqual.2009.04.005>.

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