Generalized Shifted-Factor Analysis Method for Multivariate Geo-Referenced Data |
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Authors: | William F. Christensen and Yasuo Amemiya |
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Affiliation: | (1) Department of Statistical Science, Southern Methodist University, Dallas, Texas, 75275-0332;(2) Department of Statistics, Iowa State University, Ames, Iowa, 50011-1210 |
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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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Keywords: | latent variable modeling spatial data lagged dependencies |
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