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Geo597 Geostatistics

Point Estimation. In the last chapter, we looked at estimating a mean value over a large area within which there are many samples.Eventually we need to estimate unknown values at specific locations, using weighted linear combinations.In addition to clustering, we have to account for the distance t

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Geo597 Geostatistics

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    1. Geo597 Geostatistics Ch11 Point Estimation

    2. Point Estimation In the last chapter, we looked at estimating a mean value over a large area within which there are many samples. Eventually we need to estimate unknown values at specific locations, using weighted linear combinations. In addition to clustering, we have to account for the distance to the nearby samples.

    3. In This Chapter Four methods for point estimation, polygons, triangulation, local sample means, and inverse distance. Statistical tools to evaluate the performance of these methods.

    4. Polygon Same as the polygonal declustering method for global estimation. The value of the closest sample point is simply chosen as the estimate of the point of interest. It can be viewed as a weighted linear combination with all the weights given to a single sample, the closest one.

    5. Polygon ... As long as the point of interest falls within the same polygon of influence, the polygonal estimate remains the same.

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