TY - JOUR
T1 - Estimation of sill matrices in the linear model of coregionalization
AU - Oman, Samuel D.
AU - Vakulenko-Lagun, Bella
PY - 2009
Y1 - 2009
N2 - When using least squares to fit the linear model of coregionalization to multivariate geostatistical data, the sill matrices for the different regions must be estimated, subject to the constraint that they be non-negative definite. In 1992, Goulard and Voltz proposed and empirically examined an iterative algorithm for doing this. Although no proof was given for its convergence or for the uniqueness of the solution to the problem, the algorithm has subsequently been extensively and successfully used. In this paper, we prove that the minimization problem, in fact, has a unique solution and that the algorithm is guaranteed to converge to it from any starting point. We also discuss the effect of the starting point on the speed of convergence.
AB - When using least squares to fit the linear model of coregionalization to multivariate geostatistical data, the sill matrices for the different regions must be estimated, subject to the constraint that they be non-negative definite. In 1992, Goulard and Voltz proposed and empirically examined an iterative algorithm for doing this. Although no proof was given for its convergence or for the uniqueness of the solution to the problem, the algorithm has subsequently been extensively and successfully used. In this paper, we prove that the minimization problem, in fact, has a unique solution and that the algorithm is guaranteed to converge to it from any starting point. We also discuss the effect of the starting point on the speed of convergence.
KW - Algorithm
KW - Convergence
KW - Direct and cross semivariograms
KW - Linear model of coregionalization
KW - Quadratic functions
UR - http://www.scopus.com/inward/record.url?scp=58249089302&partnerID=8YFLogxK
U2 - 10.1007/s11004-008-9190-4
DO - 10.1007/s11004-008-9190-4
M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???
AN - SCOPUS:58249089302
SN - 1874-8961
VL - 41
SP - 15
EP - 27
JO - Mathematical Geosciences
JF - Mathematical Geosciences
IS - 1
ER -