The article presents a method called quasi maximum likelihood for analyzing large sets of time series data. The researchers found that this method is effective for estimating common factors in datasets with many variables and observations. The approach is robust to errors in how the data points are related to each other. In practical terms, this method can be easily applied using existing statistical tools.