Model-free estimation from spatial samples: A reappraisal of classical sampling theory |
| |
Authors: | J. J. de Gruijter and C. J. F. ter Braak |
| |
Affiliation: | (1) Agricultural Mathematics Group, P.O. Box 100, 6700 AC Wageningen, The Netherlands |
| |
Abstract: | A commonly held view among geostatisticians is that classical sampling theory is inapplicable to spatial sampling because spatial data are dependent, whereas classical sampling theory requires them to be independent. By comparing the assumptions and use of classical sampling theory with those of geostatistical theory, we conclude that this view is both false and unfortunate. In particular, estimates of spatial means based on classical sampling designs require fewer assumptions for their validity, and are therefore more robust, than those based on a geostatistical model. |
| |
Keywords: | Fixed population superpopulation design-based inference model-based inference spatial dependence p-unbiasedness sampling strategy |
本文献已被 SpringerLink 等数据库收录! |