Kume, Alfred, Dryden, Ian L, Le, Huiling, Wood, Andrew T.A. (2010) Statistical inference for functions of the covariance matrix in the stationary Gaussian time-orthogonal principal components model. Annals of the Institute of Statistical Mathematics, 62 (5). pp. 967-994. ISSN 0020-3157. E-ISSN 1572-9052. (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) (KAR id:30342)
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. | |
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 |
Uncontrolled keywords: | Autoregressive, Central limit theorem, Configurational entropy, Principal components, Procrustes, Sample covariance, Shape, Size-and-shape |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
Depositing User: | Alfred Kume |
Date Deposited: | 11 Oct 2012 06:47 UTC |
Last Modified: | 05 Nov 2024 10:12 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/30342 (The current URI for this page, for reference purposes) |
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