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Figure 4 | International Journal of Health Geographics

Figure 4

From: Adjusting for sampling variability in sparse data: geostatistical approaches to disease mapping

Figure 4

Maps and scatterplots of the observed, Poisson kriging estimated, and UMBME estimated rates under the Poisson assumption. Compared with the A) observed rate map, the B) Poisson kriging map displayed greater smoothing than the C) UMBME map, particularly in areas of high observed rates (cases per 1,000 persons). Meanwhile, scatterplots of the D) observed, E) Poisson kriging estimated, and F) UMBME estimated rates versus the true latent rate, X( s ), combined with MSE and LCCC calculations (Table 1), demonstrated that Poisson kriging produced the highest estimation accuracy under the Poisson assumption.

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