The principles of sampling can be synthesized in randomization, restriction and over-representation. Define a sample design – define stratification, equal/unequal selection probability, etc. – means to use prior information and it is equivalent to assume a model on the population. Several well-known sampling designs are optimal related to models that maximizes the entropy. In the Cube method the prior information are used to derive a sample that match the total or means of auxiliary variables. In this respect, the sample is called balanced. Furthermore, if distances between statistical units – based on geographical coordinates or defined via auxiliary variables – are available, it could be interesting to spread the sample in the space in order to make the design more efficient. In this perspective, new spatial sampling methods, such as the GRTS, the local pivotal method and the local cube, will be covered.
27 Novembre 2018 - Sala 34 ore 14.30
Prof. Yves Tillé - Université de Neuchatel