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Robust maximum likelihood estimation of latent class models. / Bartolucci, Francesco
; Francis, Brian; Pandolfi, Silvia et al.
Proceedings of the 30th International Workshop on Statistical Modelling: Proceedings Volume 1. ed. / Herwig Friedl; Helga Wagner. Linz, Austria: johannes Kepler University, Linz, 2015. p. 94-99.
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Bartolucci, F
, Francis, B, Pandolfi, S & Pennoni, F 2015,
Robust maximum likelihood estimation of latent class models. in H Friedl & H Wagner (eds),
Proceedings of the 30th International Workshop on Statistical Modelling: Proceedings Volume 1. johannes Kepler University, Linz, Linz, Austria, pp. 94-99.
APA
Bartolucci, F.
, Francis, B., Pandolfi, S., & Pennoni, F. (2015).
Robust maximum likelihood estimation of latent class models. In H. Friedl, & H. Wagner (Eds.),
Proceedings of the 30th International Workshop on Statistical Modelling: Proceedings Volume 1 (pp. 94-99). johannes Kepler University, Linz.
Vancouver
Author
Bibtex
@inproceedings{dfb2716551524c609c33f6ebede97add,
title = "Robust maximum likelihood estimation of latent class models",
abstract = "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.",
author = "Francesco Bartolucci and Brian Francis and Silvia Pandolfi and Fulvia Pennoni",
year = "2015",
month = jul,
language = "English",
pages = "94--99",
editor = "Herwig Friedl and Wagner, {Helga }",
booktitle = "Proceedings of the 30th International Workshop on Statistical Modelling",
publisher = "johannes Kepler University, Linz",
}
RIS
TY - GEN
T1 - Robust maximum likelihood estimation of latent class models
AU - Bartolucci, Francesco
AU - Francis, Brian
AU - Pandolfi, Silvia
AU - Pennoni, Fulvia
PY - 2015/7
Y1 - 2015/7
N2 - 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.
AB - 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.
M3 - Conference contribution/Paper
SP - 94
EP - 99
BT - Proceedings of the 30th International Workshop on Statistical Modelling
A2 - Friedl, Herwig
A2 - Wagner, Helga
PB - johannes Kepler University, Linz
CY - Linz, Austria
ER -
