We introduce a class of multivariate latent Markov models with covariates for the investigation of criminal trajectories. For the maximum likelihood estimation of these models we outline an EM-type algorithm. We also show how, by fitting a suitable sequence of nested models belonging to the proposed class, we can perform a hierarchical classification of the crimes into homogeneous groups.

Bartolucci, F., Pennoni, F. (2005). A class of multivariate latent Markov models for clustering patterns of criminal activity. In Book of Short Papers Meeting of the classification and data analysis group of the Italian Statistical Society (pp.237-240).

A class of multivariate latent Markov models for clustering patterns of criminal activity

PENNONI, FULVIA
2005

Abstract

We introduce a class of multivariate latent Markov models with covariates for the investigation of criminal trajectories. For the maximum likelihood estimation of these models we outline an EM-type algorithm. We also show how, by fitting a suitable sequence of nested models belonging to the proposed class, we can perform a hierarchical classification of the crimes into homogeneous groups.
No
abstract + slide
Criminal trajectories, EM algorithm, Hierarchical classification, Latent class model
English
CLADAG 2005 - Classification and Data Analysis
887847066X
Bartolucci, F., Pennoni, F. (2005). A class of multivariate latent Markov models for clustering patterns of criminal activity. In Book of Short Papers Meeting of the classification and data analysis group of the Italian Statistical Society (pp.237-240).
Bartolucci, F; Pennoni, F
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/53225
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