The Likelihood Ratio Statistic for Testing Spatial Independence using a Separable Covariance Matrix
2009 (English)Report (Other academic)
This paper deals with the problem of testing spatial independence for dependent observations. The sample observationmatrix is assumed to follow a matrix normal distribution with a separable covariance matrix, in other words it can be written as a Kronecker product of two positive definite matrices. Two cases are considered, when the temporal covariance is known and when it is unknown. When the temporal covariance is known, the maximum likelihood estimates are computed and the asymptotic null distribution is given. In the case when the temporal covariance is unknown the maximum likelihood estimates of the parameters are found by an iterative alternating algori
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press , 2009. , 17 p.
LiTH-MAI-R, ISSN 0348-2960 ; 2009:06
Maximum likelihood estimation, Matrix normal distribution, Testing independence
IdentifiersURN: urn:nbn:se:liu:diva-18225ISRN: LiTH-MAT-R-2009-06OAI: oai:DiVA.org:liu-18225DiVA: diva2:216906