Abstract
The predictive approach and the analysis of survey data are two topics that have only attracted a small amount of attention when compared with the traditional approach of sampling from a finite population.
Furthermore, spatial effects that are very important features in agricultural surveys are often neglected in the predictive approach to sampling, and in the analysis of survey data. The inclusion of spatial information could represent a very important challenge to be addressed by researchers in the near future.
The main aim of this chapter is to properly emphasize these two different and important topics, trying to highlight the basic ideas for developing a unified approach for geographically distributed data.
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Notes
- 1.
To avoid confusion, note that in this section the uppercase Y indicates a random vector, while the lowercase y describes the realization of Y.
- 2.
For the sake of simplicity, we have supposed that the function f(.) depends on only one parameter θ. These methods can be straightforwardly extended to the multivariate case.
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Benedetti, R., Piersimoni, F., Postiglione, P. (2015). Spatial Survey Data Modeling. In: Sampling Spatial Units for Agricultural Surveys. Advances in Spatial Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46008-5_12
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