Leveraging (large) language models for automatic topic labeling. The main function converts a list of top terms into a label for each topic. Hence, it is complementary to any topic modeling package that produces a list of top terms for each topic. While human judgement is indispensable for topic validation (i.e., inspecting top terms and most representative documents), automatic topic labeling can be a valuable tool for researchers in various scenarios.

This package provides color palettes corresponding to professional and amateur, sports teams. These can be useful in creating data graphics that are themed for particular teams.

The main function of the package aims to update lmer()'/'glmer() models depending on their warnings, so trying to avoid convergence and singularity problems.

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

This package provides a simple interface to search available data provided by Theia (<https://theia.cnes.fr>), download it, and manage it. Data can be downloaded based on a search result or from a cart file downloaded from Theia website.

Nonlinear growth models are extremely useful in gaining insight into the underlying mechanism. These models are generally mechanistic, with parameters that have biological meaning. This package allows you to fit and forecast time series data using nonlinear growth models.

This package implements an algorithm for Latent Dirichlet Allocation (LDA), Blei et at. (2003) <https://www.jmlr.org/papers/volume3/blei03a/blei03a.pdf>, using style conventions from the tidyverse', Wickham et al. (2019)<doi:10.21105/joss.01686>, and tidymodels', Kuhn et al.<https://tidymodels.github.io/model-implementation-principles/>. Fitting is done via collapsed Gibbs sampling. Also implements several novel features for LDA such as guided models and transfer learning.

Extension of funHDDC Schmutz et al. (2018) <doi:10.1007/s00180-020-00958-4> for cases including outliers by fitting t-distributions for robust groups. TFunHDDC can cluster univariate or multivariate data produced by the fda package for data using a b-splines or Fourier basis.

This package provides functions for interacting directly with the Taiwan Economic Journal API to offer data in R. For more information go to <https://api.tej.com.tw>.

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.

This package provides functions to build interactive dashboards combining the Tabler UI Kit with Shiny', making it easy to create professional-looking web applications. Tabler is fully responsive and compatible with all modern browsers. Offers customizable layouts and components built with HTML5 and CSS3'. The underlying Tabler (<https://github.com/tabler/tabler>) and Tabler Icons (<https://github.com/tabler/tabler-icons>) were pre-built from source to eliminate the need for Node.js and NPM on package installation.

Introduction of qenv S4 class, that facilitates code execution and reproducibility in teal applications.

Gives the required 2^n treatment combinations in a 2^n symmetric factorial experiment in their respective standard order.

Several datasets which describe the chef contestants in Top Chef, the challenges that they compete in, and the results of those challenges. This data is useful for practicing data wrangling, graphing, and analyzing how each season of Top Chef played out.

To make the semiparametric transformation models easier to apply in real studies, we introduce this R package, in which the MLE in transformation models via an EM algorithm proposed by Zeng D, Lin DY(2007) <doi:10.1111/j.1369-7412.2007.00606.x> and adaptive lasso method in transformation models proposed by Liu XX, Zeng D(2013) <doi:10.1093/biomet/ast029> are implemented. C++ functions are used to compute complex loops. The coefficient vector and cumulative baseline hazard function can be estimated, along with the corresponding standard errors and P values.

This package provides a model for the growth of self-limiting populations using three, four, or five parameter functions, which have wide applications in a variety of fields. The dependent variable in a dynamical modeling could be the population size at time x, where x is the independent variable. In the analysis of quantitative polymerase chain reaction (qPCR), the dependent variable would be the fluorescence intensity and the independent variable the cycle number. This package then would calculate the TWW cycle threshold.

The tmap package provides two plotting modes for static and interactive thematic maps. This package extends tmap with two additional modes based on Mapbox GL JS and MapLibre GL JS'. These modes feature interactive vector tiles, globe views, and other modern web-mapping capabilities, while maintaining a consistent tmap interface across all plotting modes.

Schedule R scripts/processes with the Windows task scheduler. This allows R users to automate R processes on specific time points from R itself.

Language specific cardinal to ordinal number conversion.

Framework to run Monte Carlo simulations over a parameter grid. Allows to parallelize the simulations. Generates plots and LaTeX tables summarizing the results from the simulation.

Fast, reproducible detection and quantitative analysis of tertiary lymphoid structures (TLS) in multiplexed tissue imaging. Implements Independent Component Analysis Trace (ICAT) index, local Ripley's K scanning, automated K Nearest Neighbor (KNN)-based TLS detection, and T-cell clusters identification as described in Amiryousefi et al. (2025) <doi:10.1101/2025.09.21.677465>.

Htmlwidget of Tippyjs to add tooltips to Shiny apps and R markdown documents.

Tautulli (<http://tautulli.com>) is a monitoring application for Plex Media Servers (<https://www.plex.tv>) which collects a lot of data about media items and server usage such as play counts. This package interacts with the Tautulli API of any specified server to get said data into R. The Tautulli API documentation is available at <https://github.com/Tautulli/Tautulli/blob/master/API.md>.

Estimates time varying regression effects under Cox type models in survival data using classification and regression tree. The codes in this package were originally written in S-Plus for the paper "Survival Analysis with Time-Varying Regression Effects Using a Tree-Based Approach," by Xu, R. and Adak, S. (2002) <doi:10.1111/j.0006-341X.2002.00305.x>, Biometrics, 58: 305-315. Development of this package was supported by NIH grants AG053983 and AG057707, and by the UCSD Altman Translational Research Institute, NIH grant UL1TR001442. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The example data are from the Honolulu Heart Program/Honolulu Asia Aging Study (HHP/HAAS).