The zoo package provides a framework for working with regular and irregular time series data. This includes the zoo class, an indexed object for storing time series data, and a set of functions for creating, preprocessing, and visualizing time series data. Similar to the ts and mts classes, the zoo class is comprised of two components:
- Data structure: A vector (for univariate time series data) or matrix (for multivariance time series data) format
- Index vector: This stores the series observation's corresponding index
On the other hand, unlike the ts class, the index of the zoo class has a flexible structure, as it can store different date and time classes, such as Date, POSIXct/lt, yearmon or yearqtr, as indices.
yearmon and yearqtr are two index classes for regular time series data. The yearmon class is suitable for representing a monthly time series when...