Vital Operational Waiting Risk (VOWR) provides tools for analysing monthly Referral-to-Treatment (RTT) panel data in healthcare systems. The package supports provider-level profiling, operational risk classification, waiting-time volatility assessment, Kaplan-Meier survival analysis, Cox proportional hazards modelling, and visualisation of time-to-threshold breach patterns. It is designed to help analysts and decision-makers identify providers with high waiting times, unstable performance, and increased risk of earlier threshold breach. The survival modelling methods follow Cox (1972) <doi:10.1111/j.2517-6161.1972.tb00899.x> and Kaplan and Meier (1958) <doi:10.1080/01621459.1958.10501452>.

This package provides raster grid logic, operations that describe a discretized rectangular domain and do not require access to materialized data. Grids are arrays with dimension and extent, and many operations are functions of dimension only: number of columns, number of rows, or they are a combination of the dimension and the extent the range in x and the range in y in that order. Here we provide direct access to this logic without need for connection to any materialized data or formats. Grid logic includes functions that relate the cell index to row and column, or row and column to cell index, row, column or cell index to position. These methods are described in Loudon, TV, Wheeler, JF, Andrew, KP (1980) <doi:10.1016/0098-3004(80)90015-1>, and implementations were in part derived from Hijmans R (2024) <doi:10.32614/CRAN.package.terra>.

This package provides a wrapped LASSO approach by integrating an ensemble learning strategy to help select efficient, stable, and high confidential variables from omics-based data. Using a bagging strategy in combination of a parametric method or inflection point search method for cut-off threshold determination. This package can integrate and vote variables generated from multiple LASSO models to determine the optimal candidates. Luo H, Zhao Q, et al (2020) <doi:10.1126/scitranslmed.aax7533> for more details.

This package provides a lightweight package for sorting version codes in various forms. No strong dependencies guaranteed.

This package provides a collection of the functions for estimation, hypothesis testing, prediction for stationary vector autoregressive models.

Visualize and compute percentiles/probabilities of normal, t, f, chi square and binomial distributions.

To computed the variability independent of mean (VIM) or variation independent of mean (VIM). The methodology can be found at Peter M Rothwell et al. (2010) <doi:10.1016/S1474-4422(10)70067-3>.

This package performs 18 omnibus tests yielding a total of 28 distinct methodological variations for testing the composite hypothesis of variance homogeneity.

This package provides a collection of utilities that grew out of day-to-day non-life actuarial work at Com-PASS Advisory. Provides helpers for building chain-ladder triangles (cumulative, decumulative, run-off, development factors with optional weighting), constructing exposure columns from policy start/end dates, parsing Czech birth numbers ('rodné Ä Ã slo') into dates, generating smooth RGB color palettes for charts, and loading multi-sheet xlsx'/'xlsb files into a list of data frames. The chain-ladder helpers follow the standard methodology of Mack (1993) <doi:10.2143/AST.23.2.2005092>.

This package provides tools for visibility analysis in geospatial data. It offers functionality to perform isovist calculations, using arbitrary geometries as both viewpoints and occluders.

Forecasting univariate time series with Variational Mode Decomposition (VMD) based time delay neural network models.For method details see Konstantin, D.and Dominique, Z. (2014). <doi:10.1109/TSP.2013.2288675>.

This package provides a suite of plots for displaying variable importance and two-way variable interaction jointly. Can also display partial dependence plots laid out in a pairs plot or zenplots style.

This package provides a set of functions for generating HTML to embed hosted video in your R Markdown documents or Shiny applications.

This package provides functions for downloading, reshaping, culling, cleaning, and analyzing fossil data from the Paleobiology Database <https://paleobiodb.org>.

Extending the functionalities of the VGAM package with additional functions and datasets. At present, VGAMextra comprises new family functions (ffs) to estimate several time series models by maximum likelihood using Fisher scoring, unlike popular packages in CRAN relying on optim(), including ARMA-GARCH-like models, the Order-(p, d, q) ARIMAX model (non- seasonal), the Order-(p) VAR model, error correction models for cointegrated time series, and ARMA-structures with Student-t errors. For independent data, new ffs to estimate the inverse- Weibull, the inverse-gamma, the generalized beta of the second kind and the general multivariate normal distributions are available. In addition, VGAMextra incorporates new VGLM-links for the mean-function, and the quantile-function (as an alternative to ordinary quantile modelling) of several 1-parameter distributions, that are compatible with the class of VGLM/VGAM family functions. Currently, only fixed-effects models are implemented. All functions are subject to change; see the NEWS for further details on the latest changes.

This package implements methods for inference on potential waning of vaccine efficacy and for estimation of vaccine efficacy at a user-specified time after vaccination based on data from a randomized, double-blind, placebo-controlled vaccine trial in which participants may be unblinded and placebo subjects may be crossed over to the study vaccine. The methods also for variant stratification and allow adjustment for possible confounding via inverse probability weighting through specification of models for the trial entry process, unblinding mechanisms, and the probability an unblinded placebo participant accepts study vaccine.

Calculates and displays Venn and Euler Diagrams.

Comparison of variance - covariance patterns using relative principal component analysis (relative eigenanalysis), as described in Le Maitre and Mitteroecker (2019) <doi:10.1111/2041-210X.13253>. Also provides functions to compute group covariance matrices, distance matrices, and perform proportionality tests. A worked sample on the body shape of cichlid fishes is included, based on the dataset from Kerschbaumer et al. (2013) <doi:10.5061/dryad.fc02f>.

This package provides tools to analyze vaccine coverage data and simulate potential disease outbreak scenarios. It allows users to calculate key epidemiological metrics such as the effective reproduction number (Re), outbreak probabilities, and expected infection counts based on county-level vaccination rates, disease characteristics, and vaccine effectiveness. The package includes historical kindergarten vaccination data for Florida counties and offers functions for generating summary tables, visualizations, and exporting the underlying plot data.

RcppArmadillo implementation for the Matlab code of the Variational Mode Decomposition and Two-Dimensional Variational Mode Decomposition'. For more information, see (i) Variational Mode Decomposition by K. Dragomiretskiy and D. Zosso in IEEE Transactions on Signal Processing, vol. 62, no. 3, pp. 531-544, Feb.1, 2014, <doi:10.1109/TSP.2013.2288675>; (ii) Two-Dimensional Variational Mode Decomposition by Dragomiretskiy, K., Zosso, D. (2015), In: Tai, XC., Bae, E., Chan, T.F., Lysaker, M. (eds) Energy Minimization Methods in Computer Vision and Pattern Recognition. EMMCVPR 2015. Lecture Notes in Computer Science, vol 8932. Springer, <doi:10.1007/978-3-319-14612-6_15>.

Comprehensive set of tools for analyzing and manipulating functional data with non-uniform lengths. This package addresses two common scenarios in functional data analysis: Variable Domain Data, where the observation domain differs across samples, and Partially Observed Data, where observations are incomplete over the domain of interest. VDPO enhances the flexibility and applicability of functional data analysis in R'. See Amaro et al. (2024) <doi:10.48550/arXiv.2401.05839>, Hernandez-Amaro et al. (2025) <doi:10.48550/arXiv.2510.26917>, and Hernandez-Amaro et al. (2026) <doi:10.48550/arXiv.2605.03633>.

This package provides access to data collected by the Ecuadorian Truth Commission. Allows users to extract and analyze systematized information for human rights research in Ecuador. The package contains datasets documenting human rights violations from 1984-2008, including victim information, violation types, perpetrators, and geographic distribution.

Visualize the trends and historical downloads from packages in the CRAN repository. Data is obtained by using the API to query the database from the RStudio CRAN mirror.

This package provides a variety of tools to allow the quantification of videos of the lymphatic vasculature taken under an operating microscope. Lymphatic vessels that have been injected with a variety of blue dyes can be tracked throughout the video to determine their width over time. Code is optimised for efficient processing of multiple large video files. Functions to calculate physiologically relevant parameters and generate graphs from these values are also included.