Different techniques are used to estimate the Hurst exponent, which measures the persistence of time series data. This study compared methods like adjusted range, 1/f power spectral density analysis, and Maximum Likelihood Estimation for estimating the Hurst exponent in chaotic and stochastic systems. The researchers found that each method has its own strengths and weaknesses, and they discussed the limitations of each approach.