Return the Hurst Exponent of the time series vector ts

HurstExponent.py

def hurst(ts):
  """
  Return the Hurst Exponent of the time series vector ts
  """
  # Create the range of lag values
  lags = range(2, 100)
  
  # Calculate the array of the variance of the lagged differences
  tau = [sqrt(std(substract(ts[lag:], ts[:-lag]))) for lag in lags]
  
  # Use linear fit to estimate the Hurst Exponent
  poly = polyfit(log(lags), log(tau), 1)
  
  # Return Hurst exponent from polyfit output
  return poly[0]*2.0