The Annals of Statistics

An Approach to Upper Bound Problems for Risks of Generalized Least Squares Estimators

Yasuyuki Toyooka and Takeaki Kariya

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Abstract

First, an approach to an upper bound for the risk matrix of GLSE's is established when the information on the parameter space of the structural parameter in the covariance matrix of the error can be utilized. Second, this result is applied to regression with (i) serial correlation and (ii) heteroscedastic covariance structure. In the heteroscedastic regression, the problem of estimating the common mean of two normal populations is studied in detail.

Article information

Source
Ann. Statist., Volume 14, Number 2 (1986), 679-690.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176349946

Digital Object Identifier
doi:10.1214/aos/1176349946

Mathematical Reviews number (MathSciNet)
MR840522

Zentralblatt MATH identifier
0609.62043

JSTOR
links.jstor.org

Subjects
Primary: 62J05: Linear regression
Secondary: 62M10: Time series, auto-correlation, regression, etc. [See also 91B84]

Keywords
GLSE heteroscedasticity intraclass correlation serial correlation upper bound for risk

Citation

Toyooka, Yasuyuki; Kariya, Takeaki. An Approach to Upper Bound Problems for Risks of Generalized Least Squares Estimators. Ann. Statist. 14 (1986), no. 2, 679--690. doi:10.1214/aos/1176349946. https://projecteuclid.org/euclid.aos/1176349946


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