# Variance Estimation with Mean Absolute Deviation (MAD)¶

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

Workflow

Algorithm

Mean Absolute Deviation

References

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