This package provides functions to impute large gaps within time series based on Dynamic Time Warping methods. It contains all required functions to create large missing consecutive values within time series and to fill them, according to the paper Phan et al. (2017), <DOI:10.1016/j.patrec.2017.08.019>. Performance criteria are added to compare similarity between two signals (query and reference).

Decompose a time series into seasonal, trend and irregular components using transformations to amplitude-frequency domain.

Dynamic path analysis with estimation of the corresponding direct, indirect, and total effects, based on Fosen et al., (2006) <doi:10.1007/s10985-006-9004-2>. The main outcome of interest is a counting process from survival analysis (or recurrent events) data. At each time of event, ordinary linear regression is used to estimate the relation between the covariates, while Aalen's additive hazard model is used for the regression of the counting process on the covariates.

Researchers carried out a series of experiments passing a number of essays to different GPT detection models. Juxtaposing detector predictions for papers written by native and non-native English writers, the authors argue that GPT detectors disproportionately classify real writing from non-native English writers as AI-generated.

This package provides functions to accompany Wayne W. Daniel's Biostatistics: A Foundation for Analysis in the Health Sciences, Tenth Edition.

Compare detrital zircon suites by uploading univariate, U-Pb age, or bivariate, U-Pb age and Lu-Hf data, in a shiny'-based user-interface. Outputs publication quality figures using ggplot2', and tables of statistics currently in use in the detrital zircon geochronology community.

This package contains the discrete nonparametric survivor function estimation algorithm of De Gruttola and Lagakos for doubly interval-censored failure time data and the discrete nonparametric survivor function estimation algorithm of Sun for doubly interval-censored left-truncated failure time data [Victor De Gruttola & Stephen W. Lagakos (1989) <doi:10.2307/2532030>] [Jianguo Sun (1995) <doi:10.2307/2533008>].

This package implements life tables, fertility and mortality indicators, decomposition methods, Lee-Carter mortality forecasting, Leslie matrices, and population pyramids for demographic analysis. Methods are described in Preston et al. (2001, ISBN:1557864519) and Ustyuzhanin (2025) <doi:10.17323/demreview.v12i4.30415>.

Extracts colonisation and branching times of island species to be used for analysis in the R package DAISIE'. It uses phylogenetic and endemicity data to extract the separate island colonists and store them.

This function provides an interface between Matlab and R in facilitating fast processing for reading and saving DICOM images.

What is funnier than a dad joke? A dad joke in R! This package utilizes the API for <https://icanhazdadjoke.com> and returns dad jokes from several API endpoints.

This package implements an algorithm to effortlessly split a column in an R data frame filled with multiple values separated by delimiters. This automates the process of creating separate columns for each unique value, transforming them into binary outcomes.

This package provides functions for the calculation and plotting of synchrony in tree growth from tree-ring width chronologies (TRW index). It combines variance-covariance (VCOV) mixed modelling with functions that quantify the degree to which the TRW chronologies contain a common temporal signal. It also implements temporal trends in spatial synchrony using a moving window. These methods can also be used with other kind of ecological variables that have temporal autocorrelation corrected.

Calculate multiple or pairwise dissimilarity for orders q = 0-N (CqN; Chao et al. 2008 <doi:10/fcvn63>) for a set of species assemblages or interaction networks.

Differential partial correlation identification with the ridge and the fusion penalties.

This package provides access to Dataverse APIs <https://dataverse.org/> (versions 4-5), enabling data search, retrieval, and deposit. For Dataverse versions <= 3.0, use the archived dvn package <https://cran.r-project.org/package=dvn>.

Probability mass function, distribution function, quantile function, random generation and parameter estimation for the discrete inverse Weibull distribution.

It contains functions to apply blockmodeling of signed (positive and negative weights are assigned to the links), one-mode and valued one-mode and two-mode (two sets of nodes are considered, e.g. employees and organizations) networks (Brusco et al. (2019) <doi:10.1111/bmsp.12192>).

This package provides an R interface to the Drogon high-performance C++ HTTP server framework (<https://github.com/drogonframework/drogon>). Offers a plumber'-style application programming interface for building REST services from R with substantially higher throughput.

An intuitive, cross-platform graphical data analysis system. It uses menus and dialogs to guide the user efficiently through the data manipulation and analysis process, and has an excel like spreadsheet for easy data frame visualization and editing. Deducer works best when used with the Java based R GUI JGR, but the dialogs can be called from the command line. Dialogs have also been integrated into the Windows Rgui.

Real life data is muddy, fuzzy and unpredictable. This makes data manipulations tedious and bringing the data to right shape alone is a major chunk of work. Functions in this package help us get an understanding of dataframes to dramatically reduces data coding time.

Loads behavioural data from the widely used Drosophila Activity Monitor System (DAMS, TriKinetics <https://trikinetics.com/>) into the rethomics framework.

This package provides a modern R binding for DataTables V2 with modular extension loading, Bootstrap 5 styling, Shiny integration (proxy, events, inline inputs), server-side processing helpers, and standalone (non-Shiny) support. Configure DataTables options directly via R lists, a 1:1 mapping to the JavaScript API.

Find, visualize and explore patterns of differential taxa in vegetation data (namely in a phytosociological table), using the Differential Value (DiffVal). Patterns are searched through mathematical optimization algorithms. Ultimately, Total Differential Value (TDV) optimization aims at obtaining classifications of vegetation data based on differential taxa, as in the traditional geobotanical approach (Monteiro-Henriques 2025, <doi:10.3897/VCS.140466>). The Gurobi optimizer, as well as the R package gurobi', can be installed from <https://www.gurobi.com/products/gurobi-optimizer/>. The useful vignette Gurobi Installation Guide, from package prioritizr', can be found here: <https://prioritizr.net/articles/gurobi_installation_guide.html>.