corr_isospec (pyleoclim.utils.correlation.corr_isospec)

pyleoclim.utils.correlation.corr_isospec(y1, y2, alpha=0.05, nsim=1000)[source]

Estimates the significance of the correlation using phase randomization

Estimates the significance of correlations between non IID time series by phase randomization of original inputs. This function creates ‘nsim’ random time series that have the same power spectrum as the original time series but random phases.

Parameters

y1 (array) – vectors of (real) numbers with identical length, no NaNs allowed
y2 (array) – vectors of (real) numbers with identical length, no NaNs allowed
alpha (float) – significance level for critical value estimation [default: 0.05]
nsim (int) – number of simulations [default: 1000]

Returns

r (float) – correlation between y1 and y2
signif (bool) – true (1) if significant; false (0) otherwise
F (float) – Fraction of time series with higher correlation coefficents than observed (approximates the p-value).

References

Ebisuzaki, W, 1997: A method to estimate the statistical

significance of a correlation when the data are serially correlated. J. of Climate, 10, 2147-2153.

Prichard, D., Theiler, J. Generating Surrogate Data for Time Series

with Several Simultaneously Measured Variables (1994) Physical Review Letters, Vol 73, Number 7 (Some Rights Reserved) USC Climate Dynamics Lab, 2012.