[Forum SIS] Workshop and Tutorial on "Quantile and M-quantile Regression"
cristina.davino
cristina.davino a unimc.it
Mer 8 Giu 2016 10:26:27 CEST
It is our pleasure to announce the final Programme of two upcoming events related to the research on Quantile and M-quantile Regression:
Workshop on
“Recent Advances in Quantile and M-quantile Regression”
July 15, 2016
Tutorial on
“Quantile and M-quantile Regression”
July 14, 2016
The workshop and the tutorial will be hosted at the University of Pisa and they will take place under the auspices of the Italian Statistical Society (SIS).
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Workshop on “Recent Advances in Quantile and M-quantile Regression”
July 15, 2016
Botanic Garden (Aula Savi ) - via Paolo Buozzi 3
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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 research networks.
Keynote speakers:
Matteo Bottai (Institute of Environmental Medicine (IMM), Karolinska Institutet)
Ray Chambers (NIASRA, University of Wollongong)
Nikos Tzavidis (Social Statistics & Demography, University of Southampton)
Programme:
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 (Universitą di Padova), Valeria Bignozzi (Sapienza Universitą di Roma), Lea Petrella (Sapienza Universitą di Roma)
10:50-11:15
Coffee break
11:15-11:45
Handling heterogeneity among units in Quantile Regression
Cristina Davino (Universitą di Macerata), Domenico Vistocco (Universitą di Cassino e del Lazio Meridionale)
11:45-12:15
Finite mixtures of quantile and M-quantile regression models
Marco Alfņ (Sapienza Universitą di Roma), M. Giovanna Ranalli (Universitą degli Studi di Perugia), Nicola Salvati (Universitą 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 (Universitą di Firenze), Carla Rampichini (Universitą 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)
14:40-15:10
Parametric modeling of quantile regression coefficient functions with censored and truncated data
Paolo Frumento (Karolinska Institutet)
15:10-15:40
An alternative approach to M-quantiles for binary data with extensions to categorical data
James Dawber (NIASRA, University of Wollongong)
15:40-16:10
Bayesian inference for generalised quantile regression models
Mauro Bernardi (Universitą di Padova), Valeria Bignozzi (Sapienza Universitą di Roma), Lea Petrella (Sapienza Universitą 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 Unit‐level Quantile Nested Error Regression Model for Domain Prediction
Timo Schmid (Freien Universität Berlin), Nikos Tzavidis (University of Southampton), Nicola Salvati (Universitą di Pisa), Beate Weidenhammer (Freien Universität Berlin)
17:30-18:00
Semiparametric M-quantile modeling for indoor radon concentration
Antonella Carcagnģ, Riccardo Borgoni (Universitą di Milano Bicocca)
18:00-18:15
Conclusions
Scientific and Organizing Committee
R. Chambers (University of Wollongong), C. Davino (Universitą di Macerata), E. Fabrizi Universitą Cattolica del Sacro Cuore), C. Giusti (Universitą di Pisa), G. Marchetti (Universitą di Pisa), L. Petrella (Sapienza Universitą di Roma), N. Salvati (Universitą di Pisa), D. Vistocco (Universitą di Cassino e del Lazio meridionale)
Participation to the workshop is free but registration before June 15th will be appreciated.
We sincerely hope that you will join us and share a fruitful moment of discussion.
All the best,
Nicola Salvati (Universitą di Pisa) <mailto:nicola.salvati a unipi.it> nicola.salvati a unipi.it
Enrico Fabrizi (Universitą Cattolica del Sacro Cuore) enrico.fabrizi a unicatt.it
Cristina Davino (Universitą di Macerata) <mailto:cristina.davino a unimc.it> cristina.davino a unimc.it
About the venue: The whole workshop will take place in Aula Savi in the <https://en.wikipedia.org/wiki/Orto_botanico_di_Pisa> Botanic Garden of the University of Pisa (via Paolo Buozzi 3 – Pisa)
The Botanic Garden is in the city centre and it is marvelously well located near the <https://en.wikipedia.org/wiki/Leaning_Tower_of_Pisa> Leaning Tower, known worldwide for its unintended tilt.
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Tutorial on “Quantile and M-quantile Regression”
July 14, 2016
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Registration is closed!
The tutorial will take place in Aula Mac-Win, Dipartimento di Economia e Management, University of Pisa (via Cosimo Ridolfi 10 – Pisa)
Lecturers
Domenico Vistocco – Department of Economics and Law, University of Cassino, Italy
· Conditional mean and conditional quantiles
· The simple and multiple quantile regression model
· Sampling distribution of the quantile regression estimator
· Inference on conditional quantiles
· Equivariance property, model validation, estimation of the response conditional distribution
· Looking insight the estimation procedure: the simplex algorithm
Nikos Tzavidis (Social Statistics & Demography, University of Southampton)
· Defining robustness
· Estimating the centre (location) of a distribution
· Quantiles, M-quantiles & expectiles as location parameters
· Regression quantiles, M-quantiles & expectiles
· Robust Estimation for Generalized Linear Models
· Quantile, M-quantile, Expectile regression for discrete outcomes
· (Focusing on count outcomes)
· Quantile/M-quantile Multilevel Regression
· Using quantiles to measure heterogeneity
The school is application oriented; all the techniques will be shown in action using the software R
Schedule
9:30-13:00 Domenico Vistocco
13:00-14:00 Lunch
14:00-15:30 Domenico Vistocco
15:30-18:00 Nikos Tzavidis
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Dipartimento di Scienze politiche, della Comunicazione
e delle Relazioni internazionali
Universitą degli Studi di Macerata
Piazza Strambi, 1
62100 Macerata
Tel. 0733 2582560
e-mail: cristina.davino a unimc.it
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