Claudio GUARNACCIA | TIME SERIES ANALYSIS

cod. 8802100023

TIME SERIES ANALYSIS

	8802100023
	DEPARTMENT OF CIVIL ENGINEERING
	P.H.D. COURSE
	RISK AND SUSTAINABILITY IN CIVIL, ARCHITECTURAL AND ENVIRONMENTAL ENGINEERING SYSTEMS
	2021/2022

CURRICULUM ADVANCED TECHNOLOGIES, INFRASTRUCTURES AND TERRITORIAL SUSTAINABLE DEVELOPMENT

	YEAR OF COURSE 1
	YEAR OF DIDACTIC SYSTEM 2021
	FULL ACADEMIC YEAR

TEACHING UNITS

	SSD	CFU	HOURS	ACTIVITY	TYPE OF ACTIVITY
	FIS/07	3	21	LESSONS

PROFESSORS

	CLAUDIO GUARNACCIA T Curriculum
	ANTONIA LONGOBARDI Curriculum
	GIACOMO VICCIONE Curriculum

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

EXPECTED LEARNING RESULTS AND COMPETENCE TO ACQUIRE:
KNOWLEDGE OF STOCHASTIC PROCESSES AND OF THE TOOLS NECESSARY FOR THE RELATED EXPLORATORY ANALYSIS AND MODELLING.
KNOWLEDGE AND UNDERSTANDING:
ACQUIRE THE KNOWLEDGE NECESSARY TO UNDERSTAND THE CHARACTERISTICS AND PROPERTIES OF A STOCHASTIC PROCESS. ACQUIRE KNOWLEDGE ABOUT THE DIFFERENT MODELS USED FOR TIME SERIES SIMULATION.
KNOWLEDGE AND UNDERSTANDING APPLIED:
KNOWING HOW TO RECOGNIZE AND ANALYZE THE PROPERTIES OF A STOCHASTIC PROCESS AND KNOW HOW TO APPLY TIME SERIES SIMULATION MODELS.
AUTONOMY OF JUDGMENT:
KNOWING HOW TO IDENTIFY THE BEST TOOLS FOR THE INTERPRETATION AND MODELING OF A GIVEN STOCHASTIC PROCESS.
COMMUNICATION SKILLS:
KNOWING HOW TO ILLUSTRATE THE CHARACTERISTICS AND PROPERTIES OF A STOCHASTIC PROCESS. KNOWING HOW TO ILLUSTRATE THE CHARACTERISTICS AND PERFORMANCES OF A SIMULATION MODEL OF A STOCHASTIC PROCESS.
LEARNING ABILITY:
KNOWING HOW 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/

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Claudio GUARNACCIA | TIME SERIES ANALYSIS