Abstract
This chapter treats spatiotemporal minimum mean square error (MMSE) mapping techniques in considerable detail. Due to their popularity in many of scientific fields, we decided to include a separate chapter on MMSE techniques, despite the fact that in principle these techniques are special cases of the BME analysis. As we already discussed in the previous chapter, mapping techniques provide the tools for generating accurate predictive maps and for deductive analysis. Mapping requires important decisions regarding a few crucial issues, such as (i) the type of data to be included, (ii) the mapping objectives and (iii) the form of the estimator. The MMSE mapping techniques considered in this chapter are designed to incorporate mainly hard data. The other two issues are addressed as follows.
“The real truths are those that can be invented”.
K. Kraus
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© 1998 Springer Science+Business Media New York
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Christakos, G., Hristopulos, D.T. (1998). Spatiotemporal MMSE Mapping. In: Spatiotemporal Environmental Health Modelling: A Tractatus Stochasticus . Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-2811-8_6
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DOI: https://doi.org/10.1007/978-1-4757-2811-8_6
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-5048-2
Online ISBN: 978-1-4757-2811-8
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