Nouveaux développements en statistique spatiale/New Developments in Spatial Sampling
Date de parution
Spatial data are often autocorrelated. For the estimation of a mean or of a total, the selection of two neighboring units is inefficient because the values of the variables of interest for these units are in general similar. The analysis of a simple autocorrelated model enables us to confirm the need of spreading the sample. In spatial data, systematic sampling is considered as a very efficient strategy. Nevertheless, when the units must be selected with unequal inclusion probabilities, or when the statistical units are irregularly distributed in the space, systematic sampling cannot be implemented. Through several examples, we present a set of new methods that enable us to spread the units in the space and that satisfy given inclusion probabilities.
, 46èmes Journées de Statistique de la SFdS, ENSAI, RENNES
Type de publication
Resource Types::text::conference output::presentation