Alternative way to derive the distribution of the multivariate Ornstein–Uhlenbeck process Article Swipe
Related Concepts
ornstein–uhlenbeck process
mathematics
applied mathematics
probability density function
multivariate normal distribution
covariance
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matrix normal distribution
multivariate statistics
moment-generating function
normal-wishart distribution
covariance matrix
statistical physics
mathematical analysis
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statistics
physics
Pat Vatiwutipong
,
Nattakorn Phewchean
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1186/s13662-019-2214-1
· OA: W2957292769
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1186/s13662-019-2214-1
· OA: W2957292769
In this paper, we solve the Fokker–Planck equation of the multivariate Ornstein–Uhlenbeck process to obtain its probability density function. This approach allows us to ascertain the distribution without solving it analytically. We find that, at any moment in time, the process has a multivariate normal distribution. We obtain explicit formulae of mean, covariance, and cross-covariance matrix. Moreover, we obtain its mean-reverting condition and the long-term distribution.
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