Text book suggestion for stochastic process

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The discussion centers on an individual's preparation for independent study in Stochastic Processes and time series models, having completed two semesters of statistics and a course in multiple regression, along with experience using R. The main inquiry is whether this background is sufficient for understanding the topics and what additional knowledge might be necessary. Recommendations for textbooks that balance theory and applications include "Introductory Statistics with R" by Cryer, "Time Series -- Applications to Finance with R and S-Plus" by Chan, and "Modelling Financial Time Series with S-Plus" by Zivot and Wang. Additionally, "Introduction to Time Series and Forecasting" by Brockwell and Davis is suggested for its mathematical foundation. These resources are noted for their accessibility and relevance to finance and statistics.
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Hello. I plan on doing independent study on the Stochastic Process and time series models. I have already learned two semesters worth of statistics (Mathematical Statistics and Applications by Wackerly, Mendenhall and Scheaffer). And I have taken a semester of multiple regression models. I have used a program called R script in these classes. My question is, do I have enough knowledge to understand time series and/or the Stochastic Process. If not then what should I explore before hand? Also what are good textbooks for these topics? I would prefer a book with applications too, not just theory.

Your input will help me significantly and for that I thank you. :)
 
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Three books on R used in the context of finance and statistics are:

Cryer - Introductory Statistics with R
Chan - Time Series -- Applications to Finance with R and S-Plus
Zivot, Wang - Modelling Financial Time Series with S-Plus

And some mathematical background:

Brockwell, Davis - Introduction to Time Series and Forecasting

I find the books fairly accessible.
 
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