The Annals of Statistics

Second-Order Risk Structure of GLSE and MLE in a Regression with a Linear Process

Yasuyuki Toyooka

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Abstract

In a regression model with an error that is a general linear process, the second-order expansion of the risk matrix of GLSE or MLE is obtained. a set of sufficient conditions for the effect of estimating the structural parameter of the linear process to vanish in the above expasion is obtained. The relation of the covariance matrix of SLSE with those of GLSE and MLE up to $O(T^-2)$ is elucidated.

Article information

Source
Ann. Statist., Volume 14, Number 3 (1986), 1214-1225.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176350060

Digital Object Identifier
doi:10.1214/aos/1176350060

Mathematical Reviews number (MathSciNet)
MR856816

Zentralblatt MATH identifier
0605.62066

JSTOR
links.jstor.org

Subjects
Primary: 62F10: Point estimation
Secondary: 62J10: Analysis of variance and covariance

Keywords
GLSE Grenander's condition linear process MLE regression with a linear process second-order risk SLSE

Citation

Toyooka, Yasuyuki. Second-Order Risk Structure of GLSE and MLE in a Regression with a Linear Process. Ann. Statist. 14 (1986), no. 3, 1214--1225. doi:10.1214/aos/1176350060. https://projecteuclid.org/euclid.aos/1176350060


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