Add support for univariate monitoring

[afraniomelo]

How we are today

BibMon is based on multivariate statistical process monitoring and machine learning, aiming to establish robust monitoring procedures by identifying relevant relationships among several variables.

Proposed new feature

An important branch of process monitoring deals with univariate methods, which focus on analyzing single variables independently. Examples include statistical quality control, where individual quality metrics or operational parameters are monitored to detect deviations from established control limits (MONTGOMERY, 2012), and monitoring trends or seasonality in univariate time series, which involves analyzing patterns over time to predict future behavior and identify anomalies (ALEXANDROV, 2012).

Implementation

A new BibMon module can be implemented to handle univariate time series. This module could support the creation of various types of control charts, such as Shewhart, CUSUM, and EWMA charts, and utilize univariate time series analysis tools like Facebook's Prophet.