PISA - July 15, 2016 

The aim of the workshop is to bring together researchers interested in methodological and applied research in Quantile and M-quantile Regression. It is organized as a thematic workshop and it is expected to promote open discussions and setting-up of new research networks.

 

Final Program - YOU CAN CLICK ON THE TITLES TO VIEW/DOWNLOAD SLIDES

8.30

Registration opening

8.50

Workshop opening

9:00-9:40

Regression modeling of geometric rates

Matteo Bottai (Institute of Environmental Medicine, Karolinska Institutet)

9:40-10:20

What if…? Robust Prediction Intervals for Unbalanced Samples

Ray Chambers (NIASRA, University of Wollongong)

10:20-10:50

On the Lp-quantiles for the Student t distribution

Mauro Bernardi (Università di Padova), Valeria Bignozzi (Sapienza Università di Roma), Lea Petrella (Sapienza Università di Roma)

10:50-11:15

Coffee break

11:15-11:45

Handling heterogeneity among units in Quantile Regression

Cristina Davino (Università di Macerata), Domenico Vistocco (Università di Cassino e del Lazio Meridionale)

11:45-12:15

Finite mixtures of quantile and M-quantile regression models

Marco Alfò (Sapienza Università di Roma), M. Giovanna Ranalli (Università degli Studi di Perugia), Nicola Salvati (Università di Pisa)

12:15-12:45

Statistical modelling of gained university credits to evaluate the role of pre-enrolment assessment tests: An approach based on quantile regression for counts

Leonardo Grilli (Università di Firenze), Carla Rampichini (Università di Firenze), Roberta Varriale (ISTAT, Roma)

12:45-14:00

Lunch

 

 

 

14:00-14:40

Estimation and Testing in M-quantile Regression with application to small area estimation

Nikos Tzavidis (Social Statistics & Demography, University of Southampton), Annamaria Bianchi (University of Bergamo), Enrico Fabrizi (Catholic University of the Sacred Heart), Nicola Salvati (University of Pisa)

14:40-15:10

Parametric modeling of quantile regression coefficient functions

Paolo Frumento (Karolinska Institutet)

15:10-15:40

M-quantiles for binary and categorical data

James Dawber (NIASRA, University of Wollongong)

15:40-16:10

Bayesian inference for generalised quantile regression models

Mauro Bernardi (Università di Padova), Valeria Bignozzi (Sapienza Università di Roma), Lea Petrella (Sapienza Università di Roma)

16:10-16:30

Coffee break

16:30-17:00

Measuring Efficiency in a Spatial Context Through Quantile Regression

R.Benedetti (Università G. D’Annunzio di Chieti-Pescara), A.G. Billé (Università Tor Vergata Roma), F. Piersimoni (ISTAT), C. Salvioni (Università G. D’Annunzio di Chieti-Pescara)

17:00-17:30

A Unitlevel Quantile Nested Error Regression Model for Domain Prediction

Timo Schmid (Freien Universität Berlin), Nikos Tzavidis (Social Statistics & Demography, University of Southampton), Nicola Salvati (Università di Pisa), Beate Weidenhammer (Freien Universität Berlin)

17:30-18:00

Latent drop-out classes in linear quantile hidden Markov models

M. Francesca Marino (Università degli Studi di Perugia), Nikos Tzavidis (Social Statistics & Demography, University of Southampton), Marco Alfò (Sapienza Università di Roma)

18:00-18:15

Conclusions

 

 Scientific and Organizing Committee 

  • R. Chambers (University of Wollongong)
  • C. Davino (Università di Macerata),
  • E. Fabrizi (Università Cattolica del Sacro Cuore),
  • C. Giusti (Università di Pisa),
  • G. Marchetti (Università di Pisa),
  • L. Petrella (Sapienza Università di Roma),
  • N. Salvati (Università di Pisa),
  • D. Vistocco (Università di Cassino e del Lazio meridionale)

      

Contact information

  • Nicola Salvati (Università di Pisa) This email address is being protected from spambots. You need JavaScript enabled to view it.

  • Enrico Fabrizi (Università Cattolica del Sacro Cuore) This email address is being protected from spambots. You need JavaScript enabled to view it.

  • Cristina Davino (Università di Macerata) This email address is being protected from spambots. You need JavaScript enabled to view it.

 

Accommodation and further information can be found here