Claudio Agostinelli Claudio Agostinelli, PhD in Statistics

Claudio Agostinelli
Claudio Agostinelli, PhD in Statistics - University of Padua - Padua, Italy, is associate professor of
Statistics at the Department of Environmental Sciences, Informatics and Statistics at Ca' Foscari
University - Venice, Italy. He has been visiting Scholar at Columbia University, University of Buenos
Aires, University of British Columbia and Kuwait University. He is a member of the PHD program in
Management of Ca’ Foscari University, where he teaches Statistics models for management studies.
Research Areas
His areas of interests are robust statistics, data depth and directional data. Recent focuses are on
robust methods for asymmetric distributions, robust model selection procedures and robust estimation
under the independent contamination model; local depth and its applications.
Research Projects
He participated in several national research projects on among which research project funded by the
Italian Ministry of University and research: PRIN_MURST 2003-2005, 2006-2008, 2009-2011 and
Swiss National Science Foundation 2012-2014. He is also the coordinator of a project funded in the VI
scientific cooperation program between Italy and Argentina 2014-2016.
Conference Participation
He presented several talks at international top conferences such as ICORS (International Conference
on Robust Statistics) and ERCIM conferences (European Research Consortium for Informatics and
Mathematics). He was chair, invited speaker and discussant in several national and international
events.
Teaching Activities
He teaches at bachelor and postgraduate level courses in Italian and English on Probability and
Statistics, Environmental Statistics and Forecast and Simulation methods. He teaches the PhD course
in English “Statistics models for management studies”.
Editorial Boards And Scientific Committees Membership
Member of the editorial board of Computational Statistics, member of editorial board of Journal of Data
Analysis and Operational Research. Member of the Steering Committee of the International
Conference on Robust Statistics. Member of the scientific committee and organizing committee of
several national and international conferences.
Books, chapters, articles and conference papers (2009-)
Books and chapters
M. Riani, A. Cerioli, C. Agostinelli, and D. Perrotta (Editors) (2009). ICORS09 International Conference
on Robust Statistics: Book of Abstract. Libero Libri, Treviso. ISBN 978-88-903330-0-2.
C. Agostinelli and M. Salibian-Barrera (2010). Robust model selection with LARS based on Sestimators. In Y Lechevallier and G Saporta, Proceedings of COMPSTAT 2010, 19th International
Conference on Comptutational Statistics, 69-78. Physica-Verlag, Berlin, Paris. ISBN 978-3-79082603-6.
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C. Agostinelli e M. Romanazzi (2013). Ordering curves by data depth. In P. Giudici, S. Ingrassia, e M.
Vichi, curatori, Statistical Models for Data Analysis, volume XV di Studies in Classification, Data
Analysis, and Knowledge Organization, pagine 1–18. Springer International Publishing. ISBN 978-3319-00032-9. doi:10.1007/978-3-319-00032-9 1.
M. Romanazzi e C. Agostinelli (2013). Topics in data depth: robustness, dispersion and local depth. In
N. Torelli, F. Pesarin, and A. BarHen, Advances in Theoretical and Applied Statistics, Studies in
Theoretical and Applied Statistics. Springer. ISBN 978-3-642-35587-5.
Articles
C. Agostinelli (2009). Bias bound for the minimax estimator. Journal of Statistical Planning and
Inference, 139:2235-2241. doi:10.1016/j.jspi.2008.10.006.
C. Agostinelli (2009). Bounds for the bias of estimators under contamination. Sankhya, 71(1):19-34.
C. Agostinelli (2009). Estimating the model of the majority of the data. Advances and Applications in
Mathematical Sciences, 1(1):209-237. ISSN 0974-6803.
C. Agostinelli and L. Bisaglia (2010). ARFIMA processes and outliers: a weighted likelihood approach.
Journal of Applied Statistics, 37(9):1569-1584. ISSN 0266-4763. doi:10.1080/02664760903093609.
C. Agostinelli and M. Romanazzi (2011). Local depth. Journal of Statistical Planning and Inference,
141:817-830. ISSN 0378-3758. doi:10.1016/j.jspi.2010.08.001.
C. Agostinelli e Luca Greco (2012). A weighted strategy to handle likelihood uncertainty in bayesian
inference. Computational Statistics. doi:10.1007/s00180-011-0301-1.
Luiz Gustavo, R. Oliveira-Santos, Carlos A. Zucco, and C. Agostinelli (2012). Conditional circular
kernel density functions to analyze and test hypothesis in animal circadian activity. Animal Behaviour.
doi:10.1016/j.anbehav.2012.09.033.
C. Agostinelli and M. Romanazzi (2013). Nonparametric analysis of directional data based on data
depth. Environmental and Ecological Statistics, 20(2):253–270. doi:10.1007/s10651-012-0218-z.
C. Agostinelli and M. Romanazzi (2013). Asymptotics of stationary points of local simplicial depth in
the univariate case. Mathematical Methods of Statistics, 22(1):57-60.
C. Agostinelli, Alfio Marazzi, e Victor J. Yohai (2014). Robust estimates of the generalized loggamma
distribution. Technometrics, 56(1): 92-101, DOI:10.1080/00401706.2013.818578.
C. Agostinelli and Fatemah Alqallaf (2014). Robust inference in generalized linear models.
Communication in Statistics: simulation and computation. In Press.
Recent conferences, abstracts and papers
C. Agostinelli (2010). Robust statistical modelling with r. In Book of Abstract 28th European Meeting of
Statisticians, Piraeus, Athens.
C. Agostinelli e M. Romanazzi (2012). Depth analysis of directional data. In Atti della XLVI Riunione
Scientifica Roma, 20-22 giugno 2012. ISBN 978-88-6129-882-8.
L. Greco and C. Agostinelli (2012). Weighted likelihood in bayesian inference. In Atti della XLVI
Riunione Scientifica Roma, 20-22 giugno 2012. ISBN 978-88-6129-882-8.
V. Yohai C. Agostinelli e R. Maronna (2012). Robust estimation for multivariate data under the
independent contamination model. In Atti della XLVI Riunione Scientifica Roma, 20-22 giugno 2012.
ISBN 978-88-6129-882-8.
C. Agostinelli e A. Gagliardi (2013). Robustness issues in linear-circular regression models. In
Abstract Book of the 6th International Conference of the ERCIM WG on Computational and
Methodological Statistics (ERCIM 2013).
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