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Computing moments of ratios of quadratic forms in normal variables

Paolella, Marc S (2003). Computing moments of ratios of quadratic forms in normal variables. Computational Statistics & Data Analysis, 42(3):313-331.

Abstract

The accuracy and speed of numerical methods for computing the moments of a ratio of quadratic forms in normal variables is examined, with particular application to the sample autocorrelation function. Methods based on a saddlepoint approximation are demonstrated to be not only superior to existing approximations, but are numerically reliable and virtually as accurate as the method suitable for exact computations, while taking only a fraction of the time to compute. The new method also maintains its accuracy for time series models near the nonstationary border, which is of significant interest for unit-root inference and also a case for which first-order mean and variance approximations break down. As a wide variety of test statistics and their power functions arising in econometric models are expressible in the general form considered, the method should prove very useful for data analysis and model building.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Finance
Dewey Decimal Classification:330 Economics
Scopus Subject Areas:Physical Sciences > Statistics and Probability
Physical Sciences > Computational Mathematics
Physical Sciences > Computational Theory and Mathematics
Physical Sciences > Applied Mathematics
Scope:Discipline-based scholarship (basic research)
Language:English
Date:2003
Deposited On:30 Jul 2014 12:58
Last Modified:11 Jan 2025 02:41
Publisher:Elsevier
ISSN:0167-9473
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/S0167-9473(02)00213-X
Official URL:http://www.sciencedirect.com/science/article/pii/S016794730200213X
Other Identification Number:merlin-id:4478
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