EFFICIENT ESTIMATION OF MULTIVARIATE MOVING AVERAGE AUTOCOVARIANCES Academic Article

abstract

• SUMMARY: This paper proposes a method for estimating the autocovariances of a d-dimensional moving average process of order q. The estimators have the same asymptotic covariance matrix as those obtained by maximizing a Gaussian likelihood, and are obtained by performing a generalized least squares regression of the periodogram on the autocovariances, thus extending Parzen's (1971) estimators for d = 1. An application to least squares prediction is described and the results of a Monte Carlo simulation are presented. 1980 Biometrika Trust.

authors

• Newton, H. Joseph

published proceedings

• BIOMETRIKA

author list (cited authors)

• NEWTON, H. J.

citation count

• 3

publication date

• December 1980

publisher

• Oxford University Press (OUP)  Publisher

keywords

• 38 Economics
• 3802 Econometrics
• 49 Mathematical Sciences
• 4905 Statistics

Digital Object Identifier (DOI)

• 10.1093/biomet/67.1.227

start page

• 227

end page

• 231

volume

• 67

issue

• 1

URL

• http://dx.doi.org/10.1093/biomet/67.1.227