Howtosignalprocessing
- What is cross-correlation in Python?
- How do you plot a Correlogram in Python?
- How to calculate cross-correlation?
- How do you read a cross-correlation graph?
What is cross-correlation in Python?
Cross-correlation is a basic signal processing method, which is used to analyze the similarity between two signals with different lags. Not only can you get an idea of how well the two signals match with each other, but you also get the point of time or an index, where they are the most similar.
How do you plot a Correlogram in Python?
Correlogram with Matplotlib
Basically, it is done using the subplots() function to create the grid, and next building a loop to add the charts one by one.
How to calculate cross-correlation?
Cross-Correlation
It is calculated simply by multiplying and summing two-time series together. In the following example, graphs A and B are cross-correlated but graph C is not correlated to either.
How do you read a cross-correlation graph?
If the slope is positive, the cross correlation is positive; if there is a negative slope, the cross correlation is negative. This helps to identify important lags (or leads) in the process and is useful for application when there are predictors in an ARIMA model.
