Servizi per la didattica
PORTALE DELLA DIDATTICA

Statistical learning

04REURT

A.A. 2022/23

Course Language

Inglese

Degree programme(s)

Doctorate Research in Matematica Pura E Applicata - Torino

Course structure
Teaching Hours
Lezioni 18
Lecturers
Teacher Status SSD h.Les h.Ex h.Lab h.Tut Years teaching
Fontana Roberto Professore Ordinario SECS-S/01 5 0 0 0 6
Co-lectuers
Espandi

Context
SSD CFU Activities Area context
*** N/A ***    
Il corso, che ha come prerequisito la conoscenza dei fondamenti della teoria delle probabilitÓ e della statistica inferenziale, completa la formazione dello studente di dottorato su: 1. teoria dei valori estremi; 2. modelli per dati dipendenti; 3. metodi statistici per la pianificazione degli esperimenti. I metodi verranno illustrati in concreto mediante applicazioni del software R e/o SAS a problemi di tipo industriale, scientifico e gestionale, in modo da rendere il corso di interesse per un ampio spettro di studenti di dottorato
The course aims at completing the education of Ph.D. students about: 1. extreme value theory; 2. models for dependent data; 3. statistical methods for the Design of Experiments (DOE). All methods will be illustrated in practice using the R or the SAS software on applications to industrial, scientific, and management problems, in order to make the course useful and appealing to a broad audience of Ph.D. students.
Conoscenza delle basi della teoria della probabilitÓ e della statistica inferenziale.
Knowledge of the basics of probability theory and inferential statistics.
Extreme value theory: - Introduction: classical extreme value theory, peaks over threshold models, Point Process characterization of extremes - Multivariate extremes: asymptotic characterization, study of the dependence among extreme values - Extremes of stationary sequences: convergence conditions and extremal index. Models for dependent data: - introduction to Bayesian Statistics; - time-series; - spatial data; - mixtures. Design of Experiments: - orthogonal fractional factorial designs - optimal designs.
Extreme value theory: - Introduction: classical extreme value theory, peaks over threshold models, Point Process characterization of extremes - Multivariate extremes: asymptotic characterization, study of the dependence among extreme values - Extremes of stationary sequences: convergence conditions and extremal index. Models for dependent data: - introduction to Bayesian Statistics; - time-series; - spatial data; - mixtures. Design of Experiments: - orthogonal fractional factorial designs - optimal designs.
In presenza
On site
Presentazione orale
Oral presentation
P.D.2-2 - Giugno
P.D.2-2 - June
Altri Dottoratipotenzialmente interessati: - GESTIONE, PRODUZIONE E DESIGN (TORINO) - INGEGNERIA CIVILE E AMBIENTALE


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