Bayesian Nonparametrics
Models, theory and computational aspects.
Antonio Canale
Current positions
Assistant professor of Statistics,
University of Padua, Padua
Research affiliate
Collegio Carlo Alberto, Turin
Research Interests
Functional data analysis
Bayesian and frequentist FDA: prediction, clustering, and forecasting.
Models for discrete and count data
Nonparametric mixture models for counts, probit regressions.
Flexible distributions
Statistical aspects of the Skew-normal and skew-symmetric distributions.
Applications
Business, biology and life sciences, energy markets.
Data mining and machine learning
Big data and scalable algorithms, classification techniques.
Publications
Selected publications
- Canale, A., Lijoi, A., Nipoti, B., Pruenster, I., (2017), On the Pitman-Yor process with spike and slab base measure, Biometrika, 104, 681–697
- Canale, A., (2017), msBP: An R package to perform Bayesian nonparametric inference using multiscale Bernstein Polynomials mixtures, Journal of Statistical Software, 78, 6, 1-19
- Canale, A., Pruenster, I., (2017), Robustifying Bayesian nonparametric mixtures for count data, Biometrics, 73, 174-184
- Canale, A., De Blasi, P., (2017), Posterior asymptotics of nonparametric location-scale mixtures for multivariate density estimation, Bernoulli, 23, 379-404
- Canale, A., Ruggiero, M., (2016), Bayesian nonparametric forecasting of monotonic functional time series, Electronic Journal of Statistics, 10, 3265-3286.
- Canale, A., Vantini, S., (2016), Constrained Functional Time Series: Applications to the Italian Gas Market, International Journal of Forecasting, 32, 1340-1351.
- Bandyopadhyay D., Canale, A., (2016), Nonparametric spatial ordinal models for clustered periodontal data, Journal of the Royal Statistical Society, Series C, 65, 619-640.
- Canale, A., Kenne Pagui, E. C, Scarpa, B., (2016), Bayesian modeling of university first-year students’ grades after placement test, Journal of Applied Statistics, 43, 3015-3029 (an early version of this paper can be found in this arXiv working paper.)
- Kenne Pagui, E. C., Canale, A., (2016), Pairwise likelihood inference for the analysis of multivariate categorical responses, Applied Stochastic Models in Business and Industry, 32, 273-282
- Canale, A., Dunson, D. B., (2016), Multiscale Bernstein polynomials for densities, Statistica Sinica, 26, 3, 1175-1195
- Bisaglia, L., Canale, A., (2016), Bayesian nonparametric forecasting for INAR models, Computational Statistics and Data Analysis, 100, 70-78
- Canale, A., Scarpa, B., (2016), Bayesian nonparametric location-scale-shape mixtures, Test, 25, 1, 113-130
- Canale, A., (2015), A note on regions of given probability for the extended skew-normal distribution, Communications in Statistics, 44, 2507-2516
- Canale, A., Dunson, D. B., (2013), Nonparametric Bayes modelling of count processes, Biometrika, 100, 4, 801—816
- Canale, A., Dunson, D. B., (2011), Bayesian Kernel Mixtures for Counts, Journal of American Statistical Association, 106, 1528–1539
- Canale, A., (2011), Statistical aspects in the extended skew-normal model, Metron, LXIX, 3, 279—295
Software
- Canale, A., (2017), msBP: Multiscale Bernstein Polynomials for Densities, R package.
- Canale, A., (2016), rmp: Rounded Mixture Package, R package
- Kenne Pagui, E. C., Canale, A., (2014), Plordprob: Multivariate Ordered Probit Model via Pairwise Likelihood, R package.
Teaching
My courses
Orario di ricevimento:
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Lunedi 14.00-16.00;