Improving on the empirical covariance matrix using truncated PCA with white noise residuals

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dc.creatorJewson, Stephen
dc.date2005-06-07
dc.date.accessioned2026-07-07T05:55:01Z
dc.date.available2026-07-07T05:55:01Z
dc.descriptionThe empirical covariance matrix is not necessarily the best estimator for the population covariance matrix: we describe a simple method which gives better estimates in two examples. The method models the covariance matrix using truncated PCA with white noise residuals. Jack-knife cross-validation is used to find the truncation that maximises the out-of-sample likelihood score.
dc.identifierhttps://arxiv.org/abs/physics/0506055
dc.identifierhttp://arxiv.org/abs/physics/0506055
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/87172
dc.subjectAtmospheric and Oceanic Physics
dc.titleImproving on the empirical covariance matrix using truncated PCA with white noise residuals
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