corr

climpred.stats.corr(x, y, dim='time', lag=0, return_p=False)[source]

Computes the Pearson product-moment coefficient of linear correlation.

Note

This version calculates the effective degrees of freedom, accounting for autocorrelation within each time series that could fluff the significance of the correlation.

Parameters:
  • x (xarray object) – Independent variable time series or grid of time series.
  • y (xarray object) – Dependent variable time series or grid of time series
  • dim (optional str) – Correlation dimension
  • lag (optional int) – Lag to apply to correlaton, with x predicting y.
  • return_p (optional bool) – If True, return correlation coefficients as well as p values.
Returns:

Pearson correlation coefficients If return_p True, associated p values.

References

  • Wilks, Daniel S. Statistical methods in the atmospheric sciences. Vol. 100. Academic press, 2011.
  • Lovenduski, Nicole S., and Nicolas Gruber. “Impact of the Southern Annular Mode on Southern Ocean circulation and biology.” Geophysical Research Letters 32.11 (2005).