Applied Time Series Analysis and Forecasting with Python (en Inglés)

Reseña del libro

- 1. Time Series Concepts and Python. - 2. Exploratory Time Series Data Analysis. - 3. Stationary Time Series Models. - 4. ARMA and ARIMA Modeling and Forecasting. - 5. Nonstationary Time Series Models. - 6. Financial Time Series and Related Models. - 7. Multivariate Time Series Analysis. - 8. State Space Models and Markov Switching Models. - 9. Nonstationarity and Cointegrations. - 10. Modern Machine Learning Methods for Time Series Analysis.