Title: OPTIMAL SAMPLING STRATEGIES FOR MODEL CALIBRATION
Abstract: Surveys can be used to produce reliable transport forecasts. Surveys should provide insight into the average attributes of the modelled population.For the design of surveys it is necessary to decide on the sampling framework, that is to say the people that will be surveyed. When the population under consideration is not homogeneous with respect to the attribute of interest, stratified sampling may be beneficial. In this case the population is divided into homogeneous clusters from which samples of fixed size are drawn. The optimal sizes for each sample can be conveniently solved, if for each cluster the variability with respect to the unknown attribute and the size of the cluster relative to the size of the total population is known. The design of the sampling method becomes more complex, if one wants to estimate the average value of several attributes instead of one. According to the strategy described, for each attribute a set of optimal strata sizes exists. However, different attributes are surveyed within a single sampling framework in order to economize on survey costs. In this paper the problem of finding the corresponding optimal strata sizes is solved.(A) For the covering abstract of the conference see IRRD 887581.
Publication Year: 1996
Publication Date: 1996-01-01
Language: en
Type: article
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