IRAQI JOURNAL OF STATISTICAL SCIENCES

Abstract

    The transformation function model is one of the basic concepts in time series as it deals with multivariate time series. As for the design of this model, it depends on the data available in the time series and on other information in the series. Therefore, the representation of the transformation function model depends on the representation of data and the accuracy of the available information. and use this information in modeling. The research aims to identification the transformation function model of the monthly time series of crude oil barrel prices of the Organization of Petroleum Exporting Countries (OPEC) in US dollars as a series of outputs and the price of Brent oil as a series of inputs during the time period from (2005) to (2019). The transformation function model with the order (s,r,d,pn,qn)=(2,2,0,2,3) is the best for representing the data and the mean error criterion was used to know the prediction accuracy of the estimated transformation function model for nine months and its value was ME=-0.00851  negative That is, most of the errors are negative, which is evidence that the approved prediction gives optimistic results.