Antonia LONGOBARDI | TIME SERIES ANALYSIS

cod. 8862000006

TIME SERIES ANALYSIS

	8862000006
	DEPARTMENT OF CIVIL ENGINEERING
	Corso di Dottorato (D.M.226/2021)
	SYSTEMS AND INFRASTRUCTURE ENGINEERING FOR THE ENVIRONMENT, MOBILITY AND THE TERRITORY
	2023/2024

PERCORSO COMUNE

	OBBLIGATORIO
	YEAR OF COURSE 1
	YEAR OF DIDACTIC SYSTEM 2023
	FULL ACADEMIC YEAR

TEACHING UNITS

	SSD	CFU	HOURS	ACTIVITY	TYPE OF ACTIVITY
	ICAR/02	3	21	LESSONS

PROFESSORS

	ANTONIA LONGOBARDI T Curriculum
	GIACOMO VICCIONE Curriculum
	CLAUDIO GUARNACCIA Curriculum

	Objectives
	OVERALL PURPOSE KNOWLEDGE OF STOCHASTIC PROCESSES AND OF THE TOOLS NECESSARY FOR THE RELATED EXPLORATORY ANALYSIS AND MODELLING. KNOWLEDGE AND UNDERSTANDING: THE STUDENT WILL ACQUIRE THE KNOWLEDGE NECESSARY TO UNDERSTAND THE CHARACTERISTICS AND PROPERTIES OF A STOCHASTIC PROCESS. THE STUDENT WILL ACQUIRE KNOWLEDGE ABOUT THE DIFFERENT MODELS USED FOR TIME SERIES SIMULATION. KNOWLEDGE AND APPLIED UNDERSTANDING: THE STUDENT WILL BE ABLE TO TO RECOGNIZE AND ANALYZE THE PROPERTIES OF A STOCHASTIC PROCESS AND KNOW HOW TO APPLY TIME SERIES SIMULATION MODELS. AUTONOMY OF JUDGMENT: THE STUDENT WILL BE ABLE TO IDENTIFY THE BEST TOOLS FOR THE INTERPRETATION AND MODELING OF A GIVEN STOCHASTIC PROCESS. COMMUNICATION SKILLS: THE STUDENT WILL BE ABLE TO ILLUSTRATE THE CHARACTERISTICS AND PROPERTIES OF A STOCHASTIC PROCESS. THE STUDENT WILL BE ABLE TO ILLUSTRATE THE CHARACTERISTICS AND PERFORMANCES OF A SIMULATION MODEL OF A STOCHASTIC PROCESS. LEARNING ABILITY: THE STUDENT WILL BE ABLE TO APPLY THE KNOWLEDGE ACQUIRED TO CONTEXTS DIFFERENT FROM THOSE PRESENTED DURING THE COURSE.

OVERALL PURPOSE
KNOWLEDGE OF STOCHASTIC PROCESSES AND OF THE TOOLS NECESSARY FOR THE RELATED EXPLORATORY ANALYSIS AND MODELLING.
KNOWLEDGE AND UNDERSTANDING:
THE STUDENT WILL ACQUIRE THE KNOWLEDGE NECESSARY TO UNDERSTAND THE CHARACTERISTICS AND PROPERTIES OF A STOCHASTIC PROCESS. THE STUDENT WILL ACQUIRE KNOWLEDGE ABOUT THE DIFFERENT MODELS USED FOR TIME SERIES SIMULATION.
KNOWLEDGE AND APPLIED UNDERSTANDING:
THE STUDENT WILL BE ABLE TO TO RECOGNIZE AND ANALYZE THE PROPERTIES OF A STOCHASTIC PROCESS AND KNOW HOW TO APPLY TIME SERIES SIMULATION MODELS.
AUTONOMY OF JUDGMENT:
THE STUDENT WILL BE ABLE TO IDENTIFY THE BEST TOOLS FOR THE INTERPRETATION AND MODELING OF A GIVEN STOCHASTIC PROCESS.
COMMUNICATION SKILLS:
THE STUDENT WILL BE ABLE TO ILLUSTRATE THE CHARACTERISTICS AND PROPERTIES OF A STOCHASTIC PROCESS. THE STUDENT WILL BE ABLE TO ILLUSTRATE THE CHARACTERISTICS AND PERFORMANCES OF A SIMULATION MODEL OF A STOCHASTIC PROCESS.
LEARNING ABILITY:
THE STUDENT WILL BE ABLE TO APPLY THE KNOWLEDGE ACQUIRED TO CONTEXTS DIFFERENT FROM THOSE PRESENTED DURING THE COURSE.

	Prerequisites
	KNOWLEDGE OF THE ELEMENTS OF STATISTICS AND PROBABILITY IS RECOMMENDED.

	Contents
	STOCHASTIC PROCESSES, STATIONARITY, STATISTICAL TESTS FOR STATIONARITY, AUTOCORRELATION FUNCTIONS, TIME SERIES DECOMPOSITION, REGRESSION ANALYSIS, REGRESSION TECHNIQUES, LINEAR AND NON-LINEAR REGRESSION, MULTIPLE REGRESSION, ARIMA PROCESSES, SARIMA PROCESSES, CONSTRUCTION OF ARIMA MODELS, APPLICATION EXAMPLES.

	Teaching Methods
	THE TEACHING OF A TOTAL OF 3 CFU / 21 HOURS, IS DIVIDED INTO LECTURES (2 CFU / 14 HOURS) AND EXERCISES (1 CFU / 7 HOURS). A GROUP ACTIVITY TO BE DISCUSSED AT THE FINAL INTERVIEW IS ALSO PLANNED.

	Verification of learning
	THE ACHIEVEMENT OF THE TRAINING OBJECTIVES WILL BE ASSESSED THROUGH A FINAL INTERVIEW.

	Texts
	NOTES OF THE LESSONS PROVIDED BY THE TEACHERS.

	More Information
	HTTPS://WWW.DICIV.UNISA.IT/EN/TEACHING HTTPS://RISDICIV.IT/

BETA VERSION Data source ESSE3 [Ultima Sincronizzazione: 2024-11-05]

Antonia LONGOBARDI | TIME SERIES ANALYSIS