Isotropic Spectral Additive Models of the Covariogram

Autor:	Miro Powojowski
Rok vydání:	2008
Předmět:	Statistics and Probability Estimation of covariance matrices Covariance function Calculus Estimator Rational quadratic covariance function Applied mathematics Maximum entropy spectral estimation Density estimation Statistics Probability and Uncertainty Covariance Additive model Mathematics
Zdroj:	Journal of the Royal Statistical Society Series B: Statistical Methodology. 70:739-753
ISSN:	1467-9868 1369-7412
DOI:	10.1111/j.1467-9868.2008.00653.x
Popis:	Summary A class of additive covariance models of an isotropic random process is proposed, motivated by the spectral representation of the covariance function. Model parameters are estimated by using a special case of the minimum norm quadratic estimation estimator, whose asymptotic moments have convenient expressions in terms of spectral densities. Fitting a model in this class is equivalent to fitting an additive model of the spectral density. The class of spectral additive models proposed is dense in the set of summable covariance functions having a spectral density, allowing approximately unbiased estimation of an arbitrary covariance function and its spectral density. Theoretical results are supported by numerical comparison with commonly used models. A procedure to assist model selection is proposed. The techniques are illustrated with an application to contaminant data.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::d2015e8415f3644e5cd4ce6d493a6f80 https://doi.org/10.1111/j.1467-9868.2008.00653.x Zobrazit plný text záznamu Plný text ve formátu PDF