Declustering of clustered preferential sampling for histogram and semivariogram inference
Mathematical Geology
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Abstract
Measurements of attributes obtained more as a consequence of business ventures than sampling design frequently result in samplings that are preferential both in location and value, typically in the form of clusters along the pay. Preferential sampling requires preprocessing for the purpose of properly inferring characteristics of the parent population, such as the cumulative distribution and the semivariogram. Consideration of the distance to the nearest neighbor allows preparation of resampled sets that produce comparable results to those from previously proposed methods. Clustered sampling of size 140, taken from an exhaustive sampling, is employed to illustrate this approach. ?? International Association for Mathematical Geology 2007.
Suggested Citation
Olea, R., 2007, Declustering of clustered preferential sampling for histogram and semivariogram inference: Mathematical Geology, v. 39, no. 5, p. 453-467, https://doi.org/10.1007/s11004-007-9108-6.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Declustering of clustered preferential sampling for histogram and semivariogram inference |
| Series title | Mathematical Geology |
| DOI | 10.1007/s11004-007-9108-6 |
| Volume | 39 |
| Issue | 5 |
| Publication Date | August 22, 2007 |
| Year Published | 2007 |
| Language | English |
| Larger Work Type | Article |
| Larger Work Subtype | Journal Article |
| Larger Work Title | Mathematical Geology |
| First page | 453 |
| Last page | 467 |