[Forum SIS] DEI - Università di Catania: AVVISO DI SEMINARIO

[antonio punzo]

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AVVISO DI SEMINARIO
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Il Dipartimento di Economia e Impresa dell’Università di Catania ha
organizzato il seminario:



*DYNAMIC MIXTURES OF FACTOR ANALYZERS TO CHARACTERIZE MULTIVARIATE AIR
POLLUTANT EXPOSURES*

*Prof. Antonello MARUOTTI*

* Dipartimento di Giurisprudenza, Economia, Politica e Lingue moderne *

*Università di Roma LUMSA*





Mercoledì 31 Gennaio dalle ore 11:30

In Aula 1



Università di Catania

Palazzo delle Scienze, Corso Italia, 55, Catania





*Abstract*:



The assessment of pollution exposure is based on the analysis of a
multivariate time series that include the concentrations of several
pollutants as well as the measurements of multiple atmospheric variables.
It typically requires methods of dimensionality reduction that are capable
of identifying potentially dangerous combinations of pollutants and
simultaneously segmenting exposure periods according to air quality
conditions. When the data are high-dimensional, however, efficient methods
of dimensionality reduction are challenging because of the formidable
structure of cross-correlations that arise from the dynamic interaction
between weather conditions and natural/anthropogenic pollution sources. In
order to assess pollution exposure in an urban area while taking the above
mentioned difficulties into account, we have developed a class of
parsimonious hidden Markov models. In a multivariate time series setting,
this approach simultaneously allows for the performance of temporal
segmentation and dimensionality reduction. We specifically approximate the
distribution of multiple pollutant concentrations by mixtures of factor
analysis models, whose parameters evolve according to a latent Markov
chain. Covariates are included as predictors of the chain transition
probabilities. Parameter constraints on the factorial component of the
model are exploited to tune the flexibility of dimensionality reduction. In
order to estimate the model parameters efficiently, we have proposed a
novel three-step Alternating Expected Conditional Maximization (AECM)
algorithm, which is also assessed in a simulation study. In the case study,
the proposed methods could (1) describe the exposure to pollution in terms
of a few latent regimes, (2) associate these regimes with specific
combinations of pollutant concentration levels as well as distinct
correlation structures between concentrations, and (3) capture the
influence of weather conditions on transitions between regimes.



Paper scaricabile da: https://projecteuclid.org/euclid.aoas/1507168842





I colleghi interessati sono cordialmente invitati a partecipare.




Antonio Punzo

-- 
Antonio Punzo, Ph.D.
Associate Professor of Statistics
University of Catania
Department of Economics and Business
Corso Italia 55, 95129 Catania - Italy

Office: +39 095 7537640
e-mail: antonio.punzo a unict.it
URL: http://www.economia.unict.it/punzo
Skype: antoniopunzo81
Web: google scholar
<http://scholar.google.com/citations?user=WmIbxWkAAAAJ&hl=en>
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