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The imputation tool fills in data gaps, i.e., missing measurements in the data series. Mestro continuously fills in missing values for heating, cooling, and electricity meters by combining meter history with external variables such as outdoor temperature, time of day, and season. We continuously update our calculation method so that the imputed values reflect actual usage as accurately as possible when data points are missing. If we cannot find a strong enough correlation between usage and external variables, we do not fill in the values because we are not confident in the accuracy of the estimates.
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The chart in this tab mirrors the report’s graph but with imputed values highlighted in purple.
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- Original value
- Amount filled in
- Total – per measurement type.
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