Introduction to Time Series Modeling With Applications in R - With Applications in R

Introduction to Time Series Modeling: with Applications in R, Second Edition covers numerous stationary and nonstationary time series models and tools for estimating and utilizing them. The goal of this book is to enable readers to build their own models to understand, predict and master time series.

Sommario

1. Introduction and Preparatory Analysis. 2. The Covariance Function. 3. The Power Spectrum and the Periodogram. 4. Statistical Modeling. 5. The Least Squares Method. 6. Analysis of Time Series Using ARMA Models. 7. Estimation of an AR Model. 8. The Locally Stationary AR Model. 9. Analysis of Time Series with a State-Space Model. 10. Estimation of the ARMA Model. 11. Estimation of Trends. 12. The Seasonal Adjustment Model. 13. Time-Varying Coefficient AR Model. 14. Non-Gaussian State-Space Model. 15. The Sequential Monte Carlo Filter. 17. Simulations.

Info autore

Genshiro Kitagawa is a project professor at the University of Tokyo, the former Director-General of the Institute of Statistical Mathematics, and the former President of the Research Organization of Information and Systems.

Riassunto

Introduction to Time Series Modeling: with Applications in R, Second Edition covers numerous stationary and nonstationary time series models and tools for estimating and utilizing them. The goal of this book is to enable readers to build their own models to understand, predict and master time series.

Dettagli sul prodotto

• Autori: Genshiro Kitagawa, Genshiro (Institute of Statistical Mathe Kitagawa
• Editore: Taylor & Francis Ltd.
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 01.08.2022
• EAN: 9780367494247
• ISBN: 978-0-367-49424-7
• Pagine: 340
• Serie: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
• Categorie: Scienze sociali, diritto, economia > Economia > Altro; MATHEMATICS / Probability & Statistics / General, BUSINESS & ECONOMICS / Econometrics, Economic statistics, Probability & statistics, Mathematical & statistical software, Probability and statistics, COMPUTERS / Data Science / Data Modeling & Design, Econometrics and economic statistics, Mathematical and statistical software, EDUCATION / Teaching / Subjects / Mathematics