This package provides a ggplot2 extension that provides functions for drawing chord diagrams for visualising flows between categories. The package extends ggplot2 by adding geoms and stats for drawing chord sectors, arcs, and labels.

An interactive document on the topic of goodness of fit analysis using rmarkdown and shiny packages. Runtime examples are provided in the package function as well as at <https://predanalyticssessions1.shinyapps.io/ChiSquareGOF/>.

Analyze small-sample clustered or longitudinal data with binary outcome using modified generalized estimating equations (GEE) with bias-adjusted covariance estimator. The package provides any combination of three GEE methods and 12 covariance estimators.

Variable selection for ultrahigh-dimensional ("large p small n") linear Gaussian models using a fiducial framework allowing to draw inference on the parameters. Reference: Lai, Hannig & Lee (2015) <doi:10.1080/01621459.2014.931237>.

Enhances the H2O platform by providing tools for detailed evaluation of machine learning models. It includes functions for bootstrapped performance evaluation, extended F-score calculations, and various other metrics, aimed at improving model assessment.

Estimate the proportions of the null and the reproducibility and non-reproducibility of the signal group for the input data set. The Bayes factor calculation and EM (Expectation Maximization) algorithm procedures are also included.

This package provides a static library for Imath (see <https://github.com/AcademySoftwareFoundation/Imath>), a library for functions and data types common in computer graphics applications, including a 16-bit floating-point type.

This package provides a Shiny application to estimate the sample size required for a metabolomic experiment to achieve a desired statistical power. Estimation is possible with or without available data from a pilot study.

Fits Semiparametric Promotion Time Cure Models, taking into account (using a corrected score approach or the SIMEX algorithm) or not the measurement error in the covariates, using a backfitting approach to maximize the likelihood.

Test for independence of two random vectors, learn and report the dependency structure. For more information, see Gorsky, Shai and Li Ma, Multiscale Fisher's Independence Test for Multivariate Dependence, Biometrika, accepted, January 2022.

Construct and evaluate directed tree structures that model the process of occurrence of genetic alterations during carcinogenesis as described in Szabo, A. and Boucher, K (2002) <doi:10.1016/S0025-5564(02)00086-X>.

This extension of the poems pattern-oriented modeling (POM) framework provides a collection of modules and functions customized for paleontological time-scales, and optimized for single-generation transitions and large populations, across multiple generations.

Performing Item Response Theory analysis such as parameter estimation, ability estimation, item and model fit analyse, local independence assumption, dimensionality assumption, characteristic and information curves under various models with a user friendly shiny interface.

This package provides a toolkit for working with TOML files in R while preserving formatting, comments, and structure. tomledit enables serialization of R objects such as lists, data.frames, numeric, logical, and date vectors.

Interface to the API for TreeBASE <http://treebase.org> from R. TreeBASE is a repository of user-submitted phylogenetic trees (of species, population, or genes) and the data used to create them.

An expansion of R's stats random wishart matrix generation. This package allows the user to generate singular, Uhlig and Harald (1994) <doi:10.1214/aos/1176325375>, and pseudo wishart, Diaz-Garcia, et al.(1997) <doi:10.1006/jmva.1997.1689>, matrices. In addition the user can generate wishart matrices with fractional degrees of freedom, Adhikari (2008) <doi:10.1061/(ASCE)0733-9399(2008)134:12(1029)>, commonly used in volatility modeling. Users can also use this package to create random covariance matrices.

Uses convolution-based techniques to generate simulated camera bokeh, depth of field, and other camera effects, using an image and an optional depth map. Accepts both filename inputs and in-memory array representations of images and matrices, including common raster formats such as JPEG', PNG', TIFF', TGA', BMP', PSD', GIF', HDR', PIC', PNM', DNG', and EXR'. Includes functions to perform 2D convolutions, color correction, colorspace conversion, image/matrix reorientation and resizing, image and text overlays, exposure adjustment, camera vignette effects, and image titles.

This package provides an API to work with Redatam (see <https://redatam.org>) databases in both formats: RXDB (new format) and DICX (old format) and running Redatam programs written in SPC language. It's a wrapper around Redatam core and provides functions to open/close a database (redatam_open()/redatam_close()), list entities and variables from the database (redatam_entities(), redatam_variables()) and execute a SPC program and gets the results as data frames (redatam_query(), redatam_run()).

Common Dimensions (ComDim) is a multi-block method that simultaneously considers multiple data tables to find latent components that are common to all the tables as well as those specific to each data table, along with the contribution of each table to each component. See Jouan-Rimbaud Bouveresse and Rutledge (2024) <doi:10.1002/cem.3454>, Boccard and Rutledge (2013) <doi:10.1016/j.aca.2013.01.022>, and Puig-Castellvà et al. (2021) <doi:10.1016/j.chemolab.2021.104422>.

Extends the functionality of the RTMB <https://kaskr.r-universe.dev/RTMB> package by providing a collection of non-standard probability distributions compatible with automatic differentiation (AD). While RTMB enables flexible and efficient modelling, including random effects, its built-in support is limited to standard distributions. The package adds additional AD-compatible distributions, broadening the range of models that can be implemented and estimated using RTMB'. Automatic differentiation and Laplace approximation are described in Kristensen et al. (2016) <doi:10.18637/jss.v070.i05>.

This package is a r-ggplot2 extension that provides flipped components:

1. horizontal versions of r-ggplot2 stats and r-ggplot2 geoms;

2. vertical versions of r-ggplot2 positions.

Full 64-bit resolution date and time functionality with nanosecond granularity is provided, with easy transition to and from the standard POSIXct type. Three additional classes offer interval, period and duration functionality for nanosecond-resolution timestamps.

This package provides distance-based parametric bootstrap tests for clustering with spatial neighborhood information. It implements some distance measures, clustering of presence-absence, abundance and multilocus genetical data for species delimitation, nearest neighbor based noise detection.

This package provides integration of the Google Repo tool with emacs. It displays the output of the repo status command in a buffer and launches Magit from the status buffer for the project at point.