Kume, Alfred, Dryden, Ian L, Le, Huiling, Wood, Andrew T.A. (2010) Statistical inference for functions of the covariance matrix of stationary Gaussian vector time series. Annals of the Institute of Statistical Mathematics, 62 (5). pp. 967-994. ISSN 0020-3157. (doi:10.1007/s10463-008-0202-4) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication) | |
Official URL http://dx.doi.org/10.1007/s10463-008-0202-4 |
Abstract
We consider inference for functions of the marginal covariance matrix under a class of stationary vector time series models, referred to as time-orthogonal principal components models. The main application which motivated this work involves the estimation of configurational entropy from molecular dynamics simulations in computational chemistry, where current methods of entropy estimation involve calculations based on the sample covariance matrix. The theoretical results we obtain provide a basis for approximate inference procedures, including confidence interval calculations for scalar quantities of interest; these results are applied to the molecular dynamics application, and some further applications are discussed briefly.
Item Type: | Article |
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DOI/Identification number: | 10.1007/s10463-008-0202-4 |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics |
Divisions: | Faculties > Sciences > School of Mathematics Statistics and Actuarial Science > Statistics |
Depositing User: | Alfred Kume |
Date Deposited: | 11 Oct 2012 06:47 UTC |
Last Modified: | 29 May 2019 09:13 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/30342 (The current URI for this page, for reference purposes) |
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