Numerical instability of calculating inverse of spatial covariance matrices

Chae Young Lim, Chien-Hung Chen and Wei-Ying Wu

Statistics & Probability Letters, 2017, vol. 129, issue C, 182-188

Abstract: Computing an inverse of a covariance matrix is a common computational component in Statistics. For example, Gaussian likelihood function includes the inverse of a covariance matrix. For the computation of the inverse of a spatial covariance matrix, numerically unstable results can arise when the observation locations are getting denser. In this paper, we investigate when computational instability in calculating the inverse of a spatial covariance matrix makes maximum likelihood estimator unreasonable for a Matérn covariance model. Also, some possible approaches to relax such computational instability are discussed.

Keywords: MLE; Matérn covariance models; Ill-conditioned (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.spl.2017.05.019

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