The estimation of static and dynamic connectedness measures is created in a modular and user-friendly way. Besides, the time domain connectedness approaches, this package further allows to estimate the frequency connectedness approach, the joint spillover index and the extended joint connectedness approach. In addition, all connectedness frameworks can be based upon orthogonalized and generalized VAR, QVAR, LASSO VAR, Ridge VAR, Elastic Net VAR and TVP-VAR models. Furthermore, the package includes the conditional, decomposed and partial connectedness measures as well as the pairwise connectedness index, influence index and corrected total connectedness index. Finally, a battery of datasets are available allowing to replicate a variety of connectedness papers.

Provides tools to measure connection and independence between variables 
    without relying on linear models. Includes functions to compute Eta squared, 
    Chi-squared, and Cramer V. The main advantage of this package is that it works 
    without requiring parametric assumptions. The methods implemented are based on 
    educational material and statistical decomposition techniques, not directly on 
    previously published software or articles.

Enables 'DBI' compliant packages to integrate with the 'RStudio' connections 
  pane, and the 'pins' package. It automates the display of schemata, tables, views, as well 
  as the preview of the table's top 1000 records.

Connect to WFP's Moda platform to R, download data, and obtain the list of individuals with access to the project along with their access level.

Provides a consistent interface for connecting R to various 
    data sources including file systems and databases. 
    Designed for clinical research, 'connector' streamlines access to 'ADAM', 
    'SDTM' for example. It helps to deal with multiple data formats through a standardized API and centralized 
    configuration.

Expands the 'connector' <https://github.com/NovoNordisk-OpenSource/connector> package and provides a convenient
    interface for accessing and interacting with 'Databricks' <https://www.databricks.com> volumes and
    tables directly from R.