The estimated entity-adjusted number of transactions is defined as the number of transactions between different entities, i.e. the total number of transactions excluding transactions within addresses of the same entity. Entities are defined as a cluster of addresses that are controlled by the same network entity and are estimated through advanced heuristics and Glassnode's proprietary clustering algorithms. Note that entity–based metrics are based on data science techniques and statistical information that changes over time and are therefore mutable – the data is stable, but most recent data points are subject to slight fluctuations as time progresses.

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This is the Point-in-Time (PiT) variant of Entity-Adjusted Transaction Count. PiT metrics are strictly append-only and their history is immutable. The historic data does not necessarily reflect the best current knowledge, but the information at the time when a data point was first computed. PiT metrics are ideal candidates for applications in model backtesting and related quantitative purposes. Read our article on PiT metrics for more information.