Cross-correlation peak

1. What does a peak in cross-correlation mean?
2. What is a good cross-correlation value?
3. How do you interpret cross-correlation results?
4. How do you calculate cross-correlation?

What does a peak in cross-correlation mean?

The cross-correlation plot typically produces two peaks: a peak of enrichment corresponding to the predominant fragment length (highest correlation value) and a peak corresponding to the read length (“phantom” peak).

What is a good cross-correlation value?

Cross-correlation is generally used when measuring information between two different time series. The possible range for the correlation coefficient of the time series data is from -1.0 to +1.0. The closer the cross-correlation value is to 1, the more closely the sets are identical.

How do you interpret cross-correlation results?

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.

How do you 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.