Variables are rarely, if ever, measured without error. In this paper we propose to use the Object-Oriented Bayesian Networks architecture to model measurement errors. A mixed measurement error model is introduced to model the respondent error. Then an Object-Oriented Bayesian network, implementing the model above, is developed to represent how the actually observed values are generated from the original ones. Furthermore, potentialities and possible extensions of such an approach are discussed.
Measurement Error Modelling using Object-Oriented Bayesian Networks / Marella, D.; Vicard, P.. - (2010). (Intervento presentato al convegno XLV Riunione Scientifica SIS tenutosi a Padova).
Measurement Error Modelling using Object-Oriented Bayesian Networks
Marella D.;Vicard P.
2010
Abstract
Variables are rarely, if ever, measured without error. In this paper we propose to use the Object-Oriented Bayesian Networks architecture to model measurement errors. A mixed measurement error model is introduced to model the respondent error. Then an Object-Oriented Bayesian network, implementing the model above, is developed to represent how the actually observed values are generated from the original ones. Furthermore, potentialities and possible extensions of such an approach are discussed.| File | Dimensione | Formato | |
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