Fig. 1
From: Enabling network inference methods to handle missing data and outliers
Missing data and outlier detection and correction modules. Initially, if there are missing values in the raw dataset, trimmed scores regression (TSR) method is used to impute the missing data. Then, if the dataset has extreme outliers, first a missing value is generated for the faulty observation, and secondly the observation is reconstructed using again TSR