The purpose of this thesis is to study a restricted multivariate AFRMA model, called the Homogeneous Model. This model is defined as one in which each univariate component of the multivariate model is of the same order in p and q as it is in the multivariate model.
From a mathematical respect, multivariate ARMA model is homogeneous if , and only if, its coefficient matrices are diagonal. From a physical respect, the present observation of a phenomenon can be modeled only by it s own past observation and its present and past "errors."
The estimation procedures are developed based on maximum likelihood method and on O'Connell' s method for univariate model.
The homogeneous model is evaluated by four types of data. Those data are generated reflecting different degrees of nonhomogeneity.
It is found that the homogeneous model is sensitive to departures from the homogeneous assumptions. Small departures cause no serious problem, however, large departures are serious.
| Identifer | oai:union.ndltd.org:UTAHS/oai:digitalcommons.usu.edu:etd-8056 |
| Date | 01 May 1980 |
| Creators | Tseng, Lucy Chienhua |
| Publisher | DigitalCommons@USU |
| Source Sets | Utah State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | All Graduate Theses and Dissertations |
| Rights | Copyright for this work is held by the author. Transmission or reproduction of materials protected by copyright beyond that allowed by fair use requires the written permission of the copyright owners. Works not in the public domain cannot be commercially exploited without permission of the copyright owner. Responsibility for any use rests exclusively with the user. For more information contact digitalcommons@usu.edu. |
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