Methods for Statistical Model Fitting

The course provides fundamental understanding on statistical model fitting using Maximum Likelihood Estimation (MLE) and Maximum a Posteriori (MAP) paradigms. The main topics will be: i) review on MLE and MAP; ii) Linear and Multiple Linear Regression with MLE/MAP; iii) Fisher's information matrix and Cramér-Rao bound; iv) ROC curve analysis and its probabilistic interpretation; v) Logistic Regression with MLE/MAP for classification; vi) Survival analysis and Cox proportional hazard model.