منابع مشابه
Covariance Tapering in Spatial Statistics
In the analysis of spatial data, the inverse of the covariance matrix needs to be calculated. For example, the inverse is needed for best linear unbiased prediction or kriging, and is repeatedly calculated in the maximum likelihood estimation or the Bayesian inferences. Since the spatial sample size can be quite large, operations on the large covariance matrix can be a numerical challenge if no...
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Maximum likelihood is an attractive method of estimating covariance parameters in spatial models based on Gaussian processes. However, calculating the likelihood can be computationally infeasible for large datasets, requiring O(n3) calculations for a dataset with n observations. This article proposes the method of covariance tapering to approximate the likelihood in this setting. In this approa...
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Interpolation of a spatially correlated random process is used in many areas. The best unbiased linear predictor, often called kriging predictor in geostatistical science, requires the solution of a large linear system based on the covariance matrix of the observations. In this article, we show that tapering the correct covariance matrix with an appropriate compactly supported covariance functi...
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Bandable covariance matrices are often used to model the dependence structure of variables that follow a nature order. It has been shown that the tapering covariance estimator attains the optimal minimax rates of convergence for estimating large bandable covariance matrices. The estimation risk critically depends on the choice of the tapering parameter.We develop a Stein’s Unbiased Risk Estimat...
متن کاملRegularized MMSE multiuser detection using covariance matrix tapering
The linear minimum mean-squared error (MMSE) detector for direct-sequence code-division multiple-access (DSCDMA) systems relies on the inverse of the covariance matrix of the received signal. In multiuser environments, when few samples are available for the covariance estimation, the matrix illconditioning may produce large performance degradation. In order to cope with this effect, we propose ...
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ژورنال
عنوان ژورنال: Spatial Statistics
سال: 2016
ISSN: 2211-6753
DOI: 10.1016/j.spasta.2016.03.003