• Italiano
  • English

Department of Mathematics and Applications
"Renato Caccioppoli"


Stochastic Models and Statistical Methods

Home > Courses  > Master’s Courses > Stochastic Models and Statistical Methods

Stochastic Models and Statistical Methods

Credits

6

Prerequisites

Stochastic Processes.

Examination method

Passing an oral exam.

Learning
objectives

The course aims to introduce students to the study of continuous-time stochastic processes with a discrete state space. Particular attention is paid to queueing theory through the formulation and analysis of mathematical-probabilistic and simulation models suitable for describing real systems. A further aim is to help students grasp the relevant issues involved in building stochastic models of physical, biological and economic phenomena and in their statistical analysis.

Contents

Service systems. Little’s laws. Poisson process. Birth-death processes. Markov chains. Ergodicity. Queues: M/M/1, M/M/1/K, M/M/s, M/M/∞, M/D/1, M/G/1, GI/M/s. Review of estimation theory and statistical hypothesis testing. Monte Carlo method. Simulation of random variables. Simulation of service systems.

Academic Year
2018/2019

Lecturer: Enrica PIROZZI.

Semester: second.