Minimum distance estimation in linear models with long range dependent errors.

Mukherjee, Kanchan (1994) Minimum distance estimation in linear models with long range dependent errors. Statistics and Probability Letters, 21 (5). pp. 347-355. ISSN 0167-7152

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Abstract

This paper discusses the asymptotic representations of a class of L2-distance estimators based on weighted empirical processes in a multiple linear regression model when the errors are a function of stationary Gaussian random variables that are long-range dependent. Unlike the independent errors case, the limiting distributions of the suitably normalized estimators are not always normal. The limiting distributions depend heavily on the Hermite rank of a certain class of random variables. Some ‘goodness of fit’ tests for specified error distribution are also considered.

Item Type:
Journal Article
Journal or Publication Title:
Statistics and Probability Letters
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1800/1804
Subjects:
ID Code:
65664
Deposited By:
Deposited On:
15 Jul 2013 09:10
Refereed?:
Yes
Published?:
Published
Last Modified:
01 Jan 2020 08:34