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Time series for the technical monitoring of the transportation networks include interference and omissions. Their analysis requires the special statistical analysis. Known statistical packages do not contain a full cycle for processing of large time series. The linear timeline for the processing of periodic data is not available in digital statistics.  The sliding window approach is suitable for processing of interrupted time series. Its disadvantage is the restriction on the length of the row and the sensitivity to data gaps. The graph of the time series process­ing needs the internal optimization. The necessary steps for optimizing of the time series processing graph are determined. They are as follows: store data in an internal database, build the data samples on a single time scale, sampling based on the meta-description of the series, averaging in a sliding window, calendar bindings and omission masks, generalization of graphs, storage of graphics in vector format and so on.  The conditions for the study of series are revealed such as the database, calendar structure of data, processing of the gaps, a package of numerical methods of analysis, processing in a sliding window.

Constraints of optimization of statistical analysis of data of engineerig monitoring of transport networks