Abstract
Multivariate data with spatial dependencies arise in many areas of application, including geology, precision agriculture, and ecology. For analysis of such data, a methodology based on a generalized shifted-factor model is developed. The model incorporates potential lagged dependencies between factors and observed variables, representing asymmetric spatial dependencies observed in practice. Identification and estimation issues are discussed. A prediction procedure that exploits both the multivariate and spatial dependence in the data is proposed and illustrated.
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Christensen, W.F., Amemiya, Y. Generalized Shifted-Factor Analysis Method for Multivariate Geo-Referenced Data. Mathematical Geology 33, 801–824 (2001). https://doi.org/10.1023/A:1010998730645
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DOI: https://doi.org/10.1023/A:1010998730645