Univariate time series

A univariate time series is a sequence of scalar data that represents the evolution of a single numerical variable over time. For example, the daily temperature in New York can be a univariate time series.

Univariate time series can be represented in various schemas in the TimeSeries Toolkit. All operators in the TimeSeries Toolkit support the following two schemas for univariate time series:
  • tuple<float64 value>
    • The tuple contains one scalar value and implicit timestamp information. The time series is assumed to be a regular time series.
  • tuple<timestamp time, float64 value>
    • The tuple contains one scalar value and explicit timestamp information.
Some operators in the TimeSeries Toolkit optionally support the following schemas for univariate time series:
  • tuple<list<float64> values>
    • The tuple contains a window that represents a finite temporal sequence of scalar values with implicit timestamps.
  • tuple<list<timestamp> times, list<float64> values>
    • The tuple contains a window that represents a finite temporal sequence of scalar values, which is associated with timestamps. The list of timestamps and the list of values are the same size. Each index in the timestamp list corresponds to the timestamp of the value in the same index position of the values list.