A tool for calculating and drawing "variable trees". Variable trees display information about nested subsets of a data frame.

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

Estimates the type of variables in non-quality controlled data. The prediction is based on a random forest model, trained on over 5000 medical variables with accuracy of 99%. The accuracy can hardy depend on type and coding style of data.

Contains functions for visualization univariate data: ccdplot and qddplot.

Make it easy to use 'vue' in R with helper
              dependency functions and examples.

Contains functions for analysis and summary of tidal datasets. Also provides access to tidal data collected by the National Oceanic and Atmospheric Administration's Center for Operational Oceanographic Products and Services and the Permanent Service for Mean Sea Level. For detailed description and application examples, see Hill, T.D. and S.C. Anisfeld (2021) <doi:10.6084/m9.figshare.14161202.v1> and Hill, T.D. and S.C. Anisfeld (2015) <doi:10.1016/j.ecss.2015.06.004>.

Calculates the volume under the ROC surface and its (co)variance for ordered multi-class ROC analysis as well as certain bivariate ordinal measures of association.

Offers a comprehensive set of assertion tests to help users validate the integrity of their data. 
    These tests can be used to check for specific conditions or properties within a dataset and 
    help ensure that data is accurate and reliable. 
    The package is designed to make it easy to add quality control checks to data analysis 
    workflows and to aid in identifying and correcting any errors or inconsistencies in data.

Allow R users to interact with the 'Canvas' Learning Management System (LMS) API (see
    <https://canvas.instructure.com/doc/api/all_resources.html> for details).
    It provides a set of functions to access and manipulate course data, assignments, grades, users, 
    and other resources available through the 'Canvas' API.