List of books to learn time series analysis

Recommended 

• Shumway, R. H. and Stoffer, D. S. (2006). Time Series Analysis and its Applications: with R examples. Springer.

 

Introductory books

• Brockwell, P.J. and Davis, R.A. (2002). Introduction to Time Series and Forecasting (2nd edition). Springer.

• Chatfield, C. (2004): The Analysis of Time Series: An Introduction (6th Edition). Chapman and Hall.

• Diggle, P.J. (1990). Time Series. A Biostatistical Introduction. Oxford University Press. 

• Fuller, W.A. (1996). Introduction to Statistical Time Series (2nd edition). Wiley.

• Hamilton, J.D. (1994). Time Series Analysis. Princeton University Press.

• Priestley, M.B. (1981). Spectral Analysis and Time Series. (Vol. 1: Univariate Series & Vol. 2 Multivariate Series, Prediction and Control). Academic Press.

 

Books with emphasis on special topics

• Olivier Cappe, Eric Moulines, Tobias Ryden (2006): Inference in Hidden Markov Models. Springer.

• Durbin, J. and Koopman, S.J. (2012): Time Series Analysis by State Space Methods. Oxford University Press.

• Box, G.E., Jenkins, G.M. and Reinsel, G. C. (2008). Time Series: Forecasting and Control (4th edition). Prentice Hall. New edition of the classic 1970 book by the first 2 authors which made ARIMA modeling popular.

• Percival, D. B. and Walden, A. T. (1993). Spectral Analysis for Physical Applications: Multitaper and Conventional Univariate Techniques. Cambridge University Press.

• Percival, D. B. and Walden, A. T. (2000). Wavelet Methods for Time Series Analysis. Cambridge University Press.

• Prado, R. and West, M. (2010). Time Series, Modeling, Computation and Inference. Chapman and Hall. Presents Bayesian methods.

• Tong, H. (1993). Non-linear Time Series: A Dynamical System Approach. Oxford University Press.

• Tsay, R. S. (2010). Analysis of Financial Time Series (3rd edition). Wiley. • Hyv¨arinen, A., Karhunen, J. and Oja, E. (2001): Independent Component Analysis. Wiley.