Statistics for Stochastic Processes

 prof. Liseo Brunero

 2 year - I term 

A1: Exchangeability and de Finetti's Theorem

A2: Dirichlet process priors (definitions, properties, and
applications); Other nonparametric priors.

A3: Dirichlet process mixture models – Methodology, model formulation, prior specification, posterior simulation methods
Applications in specific statistical models

A4: Dependent Nonparametric Prior Models

B1. Stationary Gaussian Processes (GP): definition and Properties

B2: Statistical Analysis of GP: ARMA modelling and extensions
 Spectral representation of time series.
 
B3: Non Stationary Time series.