Input array containing numerical values.
Lag value (τ), representing the time shift for the correlation.
result: A double representing the computed autocorrelation coefficient.
Notes: - The function assumes array_IN contains at least tao elements. - Autocorrelation is normalized by the variance of the input array. - If tao is too large (close to the array length), the estimate may be unstable due to fewer contributing terms. - The input array should have sufficient variance to avoid division by a small denominator, which can introduce numerical instability. - For time-series data, autocorrelation values near ±1 indicate strong relationships, while values near 0 suggest randomness.
Summary: Computes the autocorrelation of an input array at a specified lag (τ). The function measures how correlated a signal is with a delayed version of itself.