Collect  your data on digital marketing campaigns from Mailchimp using the 'Windsor.ai' API <https://windsor.ai/api-fields/>.

Perform a mail merge (mass email) using the message defined in 
    markdown, the recipients in a 'csv' file, and gmail as the mailing engine. 
    With this package you can parse markdown documents as the body of email, and 
    the 'yaml' header to specify the subject line of the email.  Any '{}' braces 
    in the email will be encoded with 'glue::glue()'. You can preview the email 
    in the RStudio viewer pane, and send (draft) email using 'gmailr'.

Interface to Apache Commons Email to send emails
    from R.

Allows the user to generate a friendly user interface for emails sending. 
    The user can choose from the most popular free email services ('Gmail', 'Outlook', 'Yahoo') and his default email application. 
    The package is a wrapper for the 'Mailtoui' 'JavaScript' library.  See <https://mailtoui.com/#menu> for more information.

Shiny for Open Science to visualize, share, and inventory the
    main existing human datasets for researchers.

Implements methodologies for modelling interval data by Normal
    and Skew-Normal distributions, considering appropriate parameterizations of
    the variance-covariance matrix that takes into account the intrinsic nature of
    interval data, and lead to four different possible configuration structures.
    The Skew-Normal parameters can be estimated by maximum likelihood, while Normal
    parameters may be estimated by maximum likelihood or robust trimmed maximum
    likelihood methods.

A hybrid of the K-means algorithm and a Majorization-Minimization method to introduce a robust clustering. The reference paper is: Julien Mairal, (2015) <doi:10.1137/140957639>. The two most important functions in package 'MajKMeans' are cluster_km() and cluster_MajKm(). cluster_km() clusters data without Majorization-Minimization and cluster_MajKm() clusters data with Majorization-Minimization method. Both of these functions calculate the sum of squares (SS) of clustering.