References

Books

*         Robert H. Shumway and David S. Stoffer Time Series Analysis and Its Applications With R Examples, Springer, 2016, Recommended (Links to an external site.)

*         Avishek Pal and PKS Prakash, Practical Time Series Analysis, Birmingham - Mumbai, 2017. Recommended (Links to an external site.)

*         Box, G.E.P., G.M. Jenkins and G.C. Reinsel. n Time Series Analysis, Forecasting, and Control, 3rd ed. Englewood Cliffs, NJ: Prentice Hall, 1994. (Links to an external site.)

*         Chan, N.H. (2002). Time Series: Applications to Finance. New York: Wiley.  (Links to an external site.) (Links to an external site.)

*         Fuller, W.A. Introduction to Statistical Time Series, 2nd ed. New York: Wiley, 1996.  (Links to an external site.) (Links to an external site.)

*         Harvey, A.C. Time Series Models. Cambridge, MA: MIT Press, 1997.  (Links to an external site.) (Links to an external site.)

*         P. Brockwell, R. Davis. Time Series : Theory and Methods. Springer, 1991.  (Links to an external site.) (Links to an external site.)

*         J. Cryer, K.-S. Chan. Time Series Analysis ? With Applications in R, Springer texts in Statistics.  (Links to an external site.) (Links to an external site.)

*         Param Jeet and Prashant Vats, Learning Quantitative Finance with R. Birmingham - Mumbai, 2017.  (Links to an external site.) (Links to an external site.)

*         Ruey S. Tsay. Multivariate Time Series Analysis With R and Financial Applications. John Wiley, New Jersey, 2014.  (Links to an external site.) (Links to an external site.)

R Software

*         R codes of the book Time Series: A Data Analysis Approach Using R (Links to an external site.)

*         astsa, the R rated package (Links to an external site.)

*         dygraphs package (Links to an external site.)

*         Python for R users (Links to an external site.)

*         R packages for Time series (Links to an external site.)

*         Forecasting, Principles and practice  (Links to an external site.)

*         Using R for Time Series Analysis (Links to an external site.)

*         Moving Averages (Links to an external site.)

*         Summarize Time Series Data by Month or Year Using Tidyverse Pipes in R (Links to an external site.)

*         RMarkdown (Links to an external site.)

*         MikTeX (Links to an external site.) (Windows users) or MakTeX (Links to an external site.) (Mac users)

Python

*         Anaconda (Links to an external site.)

*         A comprehensive beginner?s guide to create a Time Series Forecast (with Codes in Python and R) (Links to an external site.)

*         Subset Time Series By Dates Python Using Pandas (Links to an external site.)

*         Python Data Science Handbook (Links to an external site.)

Papers

*         GluonTS: Probabilistic Time Series Models in Python (Links to an external site.)

*         Temporal Pattern Attention for Multivariate Time Series Forecasting (Links to an external site.)

*         Neural Decomposition of Time-Series Data for Effective Generalization (Links to an external site.)

 

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A work by Dhafer Malouche

dfmalouche@gmail.com