Home > Research > Publications & Outputs > Robust maximum likelihood estimation of latent ...

Electronic data

  • robustLCA

    Accepted author manuscript, 6.04 MB, PDF document

View graph of relations

Robust maximum likelihood estimation of latent class models

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Publication date07/2015
Host publicationProceedings of the 30th International Workshop on Statistical Modelling: Proceedings Volume 1
EditorsHerwig Friedl, Helga Wagner
Place of PublicationLinz, Austria
Publisherjohannes Kepler University, Linz
Number of pages6
<mark>Original language</mark>English


We develop a suitable reweighting approach to deal with outliers when maximum likelihood estimation is used to estimate latent class models. In such a context, the EM algorithm is used and the presence of outliers and spurious observations is common. The Proposed method is motivated by an application aimed at finding clusters of offending behaviours.