Search up to a maximum of the length of the time series

firstzero_ac(y, acfv = stats::acf(y, N - 1, plot = FALSE, na.action = na.pass))

Arguments

y

the input time series

acfv

vector of autocorrelation, if exist, used to avoid repeated computation.

Value

The first zero crossing of the autocorrelation function

References

B.D. Fulcher and N.S. Jones. hctsa: A computational framework for automated time-series phenotyping using massive feature extraction. Cell Systems 5, 527 (2017).

B.D. Fulcher, M.A. Little, N.S. Jones Highly comparative time-series analysis: the empirical structure of time series and their methods. J. Roy. Soc. Interface 10, 83 (2013).

Author

Yangzhuoran Yang