Date of Award:

5-1980

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Mathematics and Statistics

Department name when degree awarded

Applied Statistics

Advisor/Chair:

Ronald V. Canfield

Abstract

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.

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