Looking for text on stochastic processes

In summary: I think the introduction to measure theory might be in there as well.In summary, a good source for background measure theory in stochastic calculus would be Feller's two volume set on probability, and getting closer to mathematics textbooks as main texts would be a good idea.
  • #1
Gridvvk
56
1
An introductory text is preferable. Topics relevant (not a deal-breaker if not covered): Poisson process, Markov chains, renewal theory, models for queuing, and reliability.

Also, in the future I'd like to dabble in stochastic calculus, but my background in measure theory is non-existent. I've heard measure theory is a necessity for stochastic calc., so what are some good sources to build a relevant background in measure theory needed for stochastic calc.?

Thanks for any feedback.

Edit: After posting this I've realized there is a section solely for learning materials. Mod. please move if post is in wrong section.
 
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  • #2
What field are you more inclined to? Science or mathematics/economy?

For science, the book

van Kampen, Stochastic Processes in Physics and Chemistry, Third Edition (North-Holland Personal Library)

https://www.amazon.com/dp/0444529659/?tag=pfamazon01-20

might be useful to you. More a collection of methods and problems than an introductory textbook, but has some interesting insights scattered throughout the text.
 
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  • #3
Thanks for the suggestion! The field I'll probably be working with is more-so mathematics/economics (finance) than actual science.

The same methods probably apply in a non-scientific setting. Would general chemistry and standard physics I & II sequence be enough background for the scientific principles in the book? I don't mind the science, but if I have to go out of my way to learn it in order to understand the math, then it might be a distraction.
 
  • #4
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  • #5
Gridvvk said:
Thanks for the suggestion! The field I'll probably be working with is more-so mathematics/economics (finance) than actual science.

The same methods probably apply in a non-scientific setting. Would general chemistry and standard physics I & II sequence be enough background for the scientific principles in the book? I don't mind the science, but if I have to go out of my way to learn it in order to understand the math, then it might be a distraction.

Then I think you better try some closer to mathematics textbook as a main text, and peek into van Kampen/others just to get broader view of things and applications.
 
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  • #6
R136a1 said:
What about Feller's excellent two volume set on probability? https://www.amazon.com/dp/0471257087/?tag=pfamazon01-20
Especially the second volume seems to have some good stuff. There might also be an introduction to measure theory in the book.

Thanks volume 1 is pretty comprehensive and meets my needs. Volume 2 talks about measures.
 
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Related to Looking for text on stochastic processes

What is a stochastic process?

A stochastic process is a mathematical model that describes the random evolution of a system over time. It is used to analyze and predict the behavior of systems that involve randomness or uncertainty.

What are the applications of stochastic processes?

Stochastic processes have a wide range of applications in fields such as finance, engineering, biology, and physics. They are used to model and analyze complex systems that involve randomness, such as stock prices, population growth, and weather patterns.

What are the types of stochastic processes?

The two main types of stochastic processes are discrete and continuous. Discrete stochastic processes have a countable number of possible outcomes, while continuous stochastic processes have an infinite number of possible outcomes.

What is the difference between a stationary and non-stationary stochastic process?

A stationary stochastic process is one in which the statistical properties, such as mean and variance, remain constant over time. A non-stationary stochastic process is one in which these properties change over time.

How are stochastic processes analyzed and predicted?

Stochastic processes are analyzed using probability theory and mathematical tools such as Markov chains, Brownian motion, and Poisson processes. Predictions are made by using these models to simulate and forecast the behavior of the system.

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