Example: Cross Correlation

A new dataset will be created, containing the lag field and the selected fields for lagging - the values of these fields are the cross correlation values. The greatest value indicates the point of greatest correlation, and therefore that corresponding lag field value is optimal, either in terms of time or row number.

Initial dataset:

Example 1: Time based

Configuration

Selection target: Field 2

Field to be used for lag calculation: Field1 and Field3

Timestamp field: Field6

Number of steps: 5

Step size: 1 second

Resulting dataset:

Greatest correlation occurs with a lag of 1 second. A negative correlation value is still valid, showing negative correlation.

Example 2: Index based

Configuration

Selection target: Field4

Fields to be used for lag calculation: Field1

Number of steps: 5

Step size: 1

Resulting dataset:

Greatest correlation occurs with a lag of 4 steps. A negative correlation value is still valid, showing negative correlation.