Séries Temporais

In the end of the course, the students should be able to:

1. Know the concept and give examples of time series.

2. Know the concept of stationary time series, with tendency or seasonality.

3. Know the concepts and calculate the function of autocovariance, autocorrelation and partial autocorrelation of a time series.

4. Know how to use seasonality or trend removal methods in order to obtain a stationary series.

5. Know the concept of stationary autoregressive (AR), moving average (MA) and autoregressive moving average (ARMA) processes.

6. Know the concept of autoregressive integrated moving average non- stationary processes (ARIMA).

7. Know how to adjust an AR, MA, ARMA and ARIMA model using the software.

8. Perform diagnostic verification for previous models.

9. Make prediction using the previous models.