Imputation

Imputation is a statistical technique used to fill in missing values within a data set by estimating or replacing them with plausible substitutes. It helps maintain data integrity and ensures that analyses or machine learning models can proceed without being adversely affected by incomplete information.

Data must be prepared before forecasting can occur. Data preparation includes accounting for, or “imputing” missing values by probabilistically generating what the missing values could be. For example, in sales forecasting, missed sales values could be imputed based on inventory data. Imputation is both necessary as a preparatory step towards creating a better and helpful to understand gaps in historical records.​