A Study of Detecting Outliers in Time Series Using Simulation


In this paper, simulations for detecting outliers and studying their effects on the values of AR(1) time series, transfer function model with one-input variable, transfer function model with two-input variables processes, and simultaneous transfer function (STF) are conducted using the STFMODEL JOINTMDL paragraph in the Scientific Computing Associate Corporation (SCA) program. A simulation of a transfer function model is conducted to check its validity. By using the SCA program, Victor Gomez and Agustin Maravall's example for detecting outliers in time series by TRAMO program is pursued.The conclusion, which we come up with, is that the presence of outliers, depending on their nature, may have a moderate to substantial impact on the effectiveness of the standard methodology for time series analysis with respect to model identification, estimation, and forecasting.