Functions solving Chapman-Kolmogorov

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Discussion Overview

The discussion centers on the Chapman-Kolmogorov equation, exploring the functions that can satisfy this equation, particularly in the context of stochastic processes. Participants are examining specific solutions and questioning the generality of these solutions, as well as the types of processes that may fulfill the equation.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant presents a specific function that satisfies the Chapman-Kolmogorov equation and questions whether other functions exist that also meet this criterion.
  • Another participant references a solution found in a document but expresses uncertainty about the generality of that solution and invites more experienced input.
  • A participant acknowledges a lack of deep knowledge in differential equations but agrees that the equation for joint probabilities appears accurate.
  • Another participant suggests that many transition densities for Markovian processes should satisfy the Chapman-Kolmogorov equation, noting that the previously mentioned solution pertains to a "raw" Brownian motion and that similar processes can arise from arithmetic or geometric processes.
  • This participant also mentions that an Ornstein-Uhlenbeck (Langevin) process can satisfy the equation, indicating a broader context of applicable processes.

Areas of Agreement / Disagreement

Participants express differing levels of confidence and knowledge regarding the solutions to the Chapman-Kolmogorov equation. While some suggest that various functions may satisfy the equation, there is no consensus on the completeness or generality of the solutions discussed.

Contextual Notes

There is uncertainty regarding the generality of the solutions presented, as well as the specific conditions under which different functions may satisfy the Chapman-Kolmogorov equation. The discussion also reflects varying levels of familiarity with the underlying mathematical concepts.

friend
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How many functions solve the Chapman-Kolmogorov equation? The Chapman-Kolmogorov equation is defined as:

f({x_n}|{x_m}) = \int_{ - \infty }^{ + \infty } {f({x_n}|{x_o})} f({x_o}|{x_m})d{x_o}

And I've seen it proved that the following function will satisfy the above condition:

f({x_n}|{x_o}) = {\left( {\frac{\lambda }{{2\pi ({t_n} - {t_0})}}} \right)^{{\raise0.5ex\hbox{$\scriptstyle 1$}<br /> \kern-0.1em/\kern-0.15em<br /> \lower0.25ex\hbox{$\scriptstyle 2$}}}}{e^{\frac{{\lambda {{({x_n} - {x_0})}^2}}}{{2({t_n} - {t_0})}}}}

But I have to wonder if there are any other functions that satisfy it. Any help is appreciated.
 
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friend said:
How many functions solve the Chapman-Kolmogorov equation? The Chapman-Kolmogorov equation is defined as:

f({x_n}|{x_m}) = \int_{ - \infty }^{ + \infty } {f({x_n}|{x_o})} f({x_o}|{x_m})d{x_o}

And I've seen it proved that the following function will satisfy the above condition:

f({x_n}|{x_o}) = {\left( {\frac{\lambda }{{2\pi ({t_n} - {t_0})}}} \right)^{{\raise0.5ex\hbox{$\scriptstyle 1$}<br /> \kern-0.1em/\kern-0.15em<br /> \lower0.25ex\hbox{$\scriptstyle 2$}}}}{e^{\frac{{\lambda {{({x_n} - {x_0})}^2}}}{{2({t_n} - {t_0})}}}}

But I have to wonder if there are any other functions that satisfy it. Any help is appreciated.

I did find this solution to the Chapman-Kolmogorov equation:

http://www.pims.math.ca/files/monahan_2b_0.pdf

Although, I could not find any reference to the author. And I don 't know how general or particular his solution is. Maybe a more experienced person would like to take a look at it and advice. Thanks.
 
I don't really know all that much about DE's (ODE's or PDE's) but that equation for joint probabilities looks pretty accurate.
 
I believe just about any transition density for a markovian process should satisfy the C-K equation.
The solution listed above was for a "raw" brownian motion. You can see that any arithmetic or geometric process will result in a similar process. The post above had a link to show that an Ornstein-Uhlenbeck (Langevin) process can satisfy it.
 

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