A mixture of Gaussian mixture models is proposed to deal with the identification of survey respondents providing values in a wrong unity measure. The "two-level" mixture model allows effective classification in a non-normal setting. The natural constraints of the problem make the model identifiable. The effectiveness of the proposal is shown by simulation studies and an application to the 1997 Italian Labour Cost Survey.
A mixture of mixture models for a classification problem: The unity measure error / DI ZIO, Marco; Guarnera, Ugo; Rocci, R. - In: COMPUTATIONAL STATISTICS & DATA ANALYSIS. - ISSN 0167-9473. - 51:5(2007), pp. 2573-2585. [10.1016/j.csda.2006.01.001]
A mixture of mixture models for a classification problem: The unity measure error
ROCCI R
2007
Abstract
A mixture of Gaussian mixture models is proposed to deal with the identification of survey respondents providing values in a wrong unity measure. The "two-level" mixture model allows effective classification in a non-normal setting. The natural constraints of the problem make the model identifiable. The effectiveness of the proposal is shown by simulation studies and an application to the 1997 Italian Labour Cost Survey.| File | Dimensione | Formato | |
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