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

This package provides tools for measuring similarity among documents and detecting passages which have been reused. Implements shingled n-gram, skip n-gram, and other tokenizers; similarity/dissimilarity functions; pairwise comparisons; minhash and locality sensitive hashing algorithms; and a version of the Smith-Waterman local alignment algorithm suitable for natural language.

This package provides a set of functions that allow users for styling their R code according to the tidyverse style guide. The package uses a native Rust implementation to ensure the highest performance. Learn more about tergo at <https://rtergo.pagacz.io>.

Enhances koRpus text object classes and methods to also support large corpora. Hierarchical ordering of corpus texts into arbitrary categories will be preserved. Provided classes and methods also improve the ability of using the koRpus package together with the tm package. To ask for help, report bugs, suggest feature improvements, or discuss the global development of the package, please subscribe to the koRpus-dev mailing list (<https://korpusml.reaktanz.de>).

Factor and autoregressive models for matrix and tensor valued time series. We provide functions for estimation, simulation and prediction. The models are discussed in Li et al (2021) <doi:10.48550/arXiv.2110.00928>, Chen et al (2020) <DOI:10.1080/01621459.2021.1912757>, Chen et al (2020) <DOI:10.1016/j.jeconom.2020.07.015>, and Xiao et al (2020) <doi:10.48550/arXiv.2006.02611>.

This package contains summary data on gene expression in normal human tissues from the Human Protein Atlas for use with the Tissue-Adjusted Pathway Analysis of cancer (TPAC) method. Frost, H. Robert (2023) "Tissue-adjusted pathway analysis of cancer (TPAC)" <doi:10.1101/2022.03.17.484779>.

Bringing business and financial analysis to the tidyverse'. The tidyquant package provides a convenient wrapper to various xts', zoo', quantmod', TTR and PerformanceAnalytics package functions and returns the objects in the tidy tibble format. The main advantage is being able to use quantitative functions with the tidyverse functions including purrr', dplyr', tidyr', ggplot2', lubridate', etc. See the tidyquant website for more information, documentation and examples.

Fit a threshold regression model based on the first-hitting-time of a boundary by the sample path of a Wiener diffusion process. The threshold regression methodology is well suited to applications involving survival and time-to-event data.

This package provides a slightly-opinionated R interface for the Tremendous API (<https://www.tremendous.com/>). In addition to supporting GET and POST requests, tremendousr has, dare I say, tremendously intuitive functions for sending digital rewards and incentives directly from R.

This package provides methods for extracting various features from time series data. The features provided are those from Hyndman, Wang and Laptev (2013) <doi:10.1109/ICDMW.2015.104>, Kang, Hyndman and Smith-Miles (2017) <doi:10.1016/j.ijforecast.2016.09.004> and from Fulcher, Little and Jones (2013) <doi:10.1098/rsif.2013.0048>. Features include spectral entropy, autocorrelations, measures of the strength of seasonality and trend, and so on. Users can also define their own feature functions.

The Twilio web service provides an API for computer programs to interact with telephony. The included functions wrap the SMS and MMS portions of Twilio's API, allowing users to send and receive text messages from R. See <https://www.twilio.com/docs/> for more information.

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.

This package provides a terribly-simple data base for numeric time series, written purely in R, so no external database-software is needed. Series are stored in plain-text files (the most-portable and enduring file type) in CSV format. Timestamps are encoded using R's native numeric representation for Date'/'POSIXct', which makes them fast to parse, but keeps them accessible with other software. The package provides tools for saving and updating series in this standardised format, for retrieving and joining data, for summarising files and directories, and for coercing series from and to other data types (such as zoo series).

This package provides functions for visualizing networks with tmap'. It supports sfnetworks objects natively but is not limited to them. Useful for adding network layers such as edges and nodes to tmap maps. More features may be added in future versions.

This package provides pipeline audit trails and data diagnostics for tidyverse workflows. The audit trail system captures lightweight metadata snapshots at each step of a pipeline, building a structured audit report without storing the data itself. Also includes diagnostic functions for interactive data analysis.

Create additional rows and columns on broom::tidy() output to allow for easier control on categorical parameter estimates.

This package provides a minimal-dependency, performance-first R package for reading, writing, validating, streaming, and converting TOON (Token-Oriented Object Notation) data. Optimized for very large tabular files with robust diagnostics. Supports lossless JSON conversion and tabular CSV/Parquet/Feather conversion.

This package provides a suite of auxiliary functions that enhance time series estimation and forecasting, including a robust anomaly detection routine based on Chen and Liu (1993) <doi:10.2307/2290724> (imported and wrapped from the tsoutliers package), utilities for managing calendar and time conversions, performance metrics to assess both point forecasts and distributional predictions, advanced simulation by allowing the generation of time series componentsâ such as trend, seasonal, ARMA, irregular, and anomaliesâ in a modular fashion based on the innovations form of the state space model and a number of transformation methods including Box-Cox, Logit, Softplus-Logit and Sigmoid.

Detection of outliers in time series following the Chen and Liu (1993) <DOI:10.2307/2290724> procedure. Innovational outliers, additive outliers, level shifts, temporary changes and seasonal level shifts are considered.

This package provides a collection of functions and routines for inputting thermal image video files, plotting and converting binary raw data into estimates of temperature. First published 2015-03-26. Written primarily for research purposes in biological applications of thermal images. v1 included the base calculations for converting thermal image binary values to temperatures. v2 included additional equations for providing heat transfer calculations and an import function for thermal image files (v2.2.3 fixed error importing thermal image to windows OS). v3. Added numerous functions for converting thermal image, videos, rewriting and exporting. v3.1. Added new functions to convert files. v3.2. Fixed the various functions related to finding frame times. v4.0. fixed an error in atmospheric attenuation constants, affecting raw2temp and temp2raw functions. Recommend update for use with long distance calculations. v.4.1.3 changed to frameLocates to reflect change to as.character() to format().

This package provides methods and tools for generating forecasts at different temporal frequencies using a hierarchical time series approach.

The Taylor Russell model is a widely used method for assessing test validity in personnel selection tasks. The three functions in this package extend this model in a number of notable ways. TR() estimates test validity for a single selection test via the original Taylor Russell model. It extends this model by allowing users greater flexibility in argument choice. For example, users can specify any three of the four parameters (base rate, selection ratio, criterion validity, and positive predictive value) of the Taylor Russell model and estimate the remaining parameter (see the help file for examples). The TaylorRussell() function generalizes the original Taylor Russell model to allow for multiple selection tests (predictors). To our knowledge, this is the first generalization of the Taylor Russell model to allow for three or more selection tests (it is also the first to correctly handle models with two selection tests). TRDemo() is a shiny program for illustrating the underlying logic of the Taylor Russell model. Taylor, HC and Russell, JT (1939) "The relationship of validity coefficients to the practical effectiveness of tests in selection: Discussion and tables" <doi:10.1037/h0057079>.

The goal of tidyplots is to streamline the creation of publication-ready plots for scientific papers. It allows to gradually add, remove and adjust plot components using a consistent and intuitive syntax.

Offers a TableContainer() function to create tables enriched with row, column, and table annotations. This package is similar to SummarizedExperiment in Bioconductor <doi:10.18129/B9.bioc.SummarizedExperiment>, but designed to work independently of Bioconductor, it ensures annotations are automatically updated when the table is subset. Additionally, it includes format_tbl() methods for enhanced table formatting and display.