Method of autoregression in application of singular-spectral analysis of time series for forecasting production of oil and gas industry products

Abstract

More and more time series data are produced in various fields. It provides data for the research of time series analysis method, and promotes the development of time series research. Due to the generation of highly complex and large-scale time series data, the construction of forecasting models for time series data brings greater challenges. The theoretical aspects of using the model of singular-spectral analysis of time series with the use of autoregression are considered, and the justification of the expediency of using this model for forecasting the production of products for both the oil and gas industry and dual-use products is given. Both autoregressive model and decision tree model can be applied with the same degree of reliability for forecasting aggregate values of production.