1st Edition
Long Memory Time Series Analysis
1. Introduction to AR, MA Time Series, Autocorrelation, Partial Autocorrelation, Spectral Density
2. ARMA Process and Box–Jenkins Model
3. Integer Differencing and ARIMA Process with White Noise
4. Fractional Differencing and ARFIMA Process with White Noise
5. Short, Intermediate, and Long Memory Properties of Time Series
6. Standard Long Memory and State Space Modeling of ARFIMA Process with White Noise
7. State Space Modeling of GARMA Processes with Generalized Long Memory
8. Nonlinear and Nonstationary Time Series
9. An Introduction to Nonparametric Long Memory Time Series
10. ARMA, ARIMA, ARFIMA, and GARMA Models with GARCH Errors
11. Enhancing Time Series Analysis with Machine Learning, High-Frequency Data, and Applications in Medicine and Biology
Biography
Gnanadarsha Sanjaya Dissanayake earned a PhD in statistics, with an emphasis on time series econometrics, at the School of Mathematics and Statistics, University of Sydney, Australia. He is the Senior Biostatistician, New South Wales Ministry of Health, and an Honorary Research Associate, School of Mathematics and Statistics, University of Sydney, Australia.
Hassan Doosti is the Program Director in the Master of Data Science program and the Senior Lecturer in Statistics, School of Mathematical and Physical Sciences, Macquarie University, Sydney, Australia. He is the author/editor of three books: Flexible Nonparametric Curve Estimation (2024), Ethics in Statistics: Opportunities and Challenges (2024), and Practical Biostatistics for Medical and Health Sciences (co-authored with Seyed Hassan Saneii; 2024).
