A simulation study of additive outlier in ARMA (1, 1) model
Document Type
Article
Publication Date
1-1-2009
Abstract
Abnormal observation due to an isolated incident such as a recording error is known as additive outlier and it is often found in time series. Since extreme value of additive outliers may contribute to the inaccuracy of model specification, proper detection procedure is significant to avoid such error. Equations that explain the nature of an additive outlier and the test statistics pertaining to it are discussed in this article. This is followed by two separate simulation studies that are conducted to investigate the sampling behavior and detection performance of the test statistics in ARMA (1, 1) models. Results for the first simulation study show that the test statistics is an increasing function of sample size. Whilst in the other simulation study we see that the performance of the test statistics improves as large magnitudes of outlier effect are used.
Keywords
Additive outlier, Detection performance of test statistics, Sampling behavior of test statistics, Simulation
Divisions
MathematicalSciences
Publication Title
International Journal of Mathematical Models and Methods in Applied Sciences
Volume
3
Issue
2
Publisher
North Atlantic University Union