Variance Estimation with Mean Absolute Deviation (MAD)ΒΆ

Non-Causal Step

This step applies the Mean Absolute Deviation (MAD) algorithm to estimate the variance of the data. The basic formula is as follows:

\[{\hat{\sigma} = K \cdot \text{MAD}}\quad\text{,}\]

where \(K \approx 1.4826\), MAD is a measure returned by the Mean Absolute Deviation (MAD) algorithm and \(\hat{\sigma}\) denotes the estimated variance.

Input Parameters

  1. Input data

Output Parameters

  1. Estimated variance




Mean Absolute Deviation


  • D.C. Hoaglin, F. Mosteller, J. W. Tukey, Understanding Robust and Exploratory Data Analysis, John Wiley and Sons, 1983.