Cox process

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In probability theory, a Cox process, also known as a doubly stochastic Poisson process is a point process which is a generalization of a Poisson process where the time-dependent intensity is itself a stochastic process. The process is named after the statistician David Cox, who first published the model in 1955.[1]


Cox processes are used to generate simulations of spike trains (the sequence of action potentials generated by a neuron),[2] and also in financial mathematics where they produce a "useful framework for modeling prices of financial instruments in which credit risk is a significant factor."[3]




Contents





  • 1 Definition


  • 2 Laplace transform


  • 3 See also


  • 4 References




Definition


Let ξdisplaystyle xi xi be a random measure.


A random measure ηdisplaystyle eta eta is called a Cox process directed by ξdisplaystyle xi xi , if L(η∣ξ=μ)displaystyle mathcal L(eta mid xi =mu )displaystyle mathcal L(eta mid xi =mu ) is a Poisson process with intensity measure μdisplaystyle mu mu .


Here, L(η∣ξ=μ)displaystyle mathcal L(eta mid xi =mu )displaystyle mathcal L(eta mid xi =mu ) is the conditional distribution of ηdisplaystyle eta eta , given ξ=μdisplaystyle xi =mu displaystyle xi =mu .



Laplace transform


If ξdisplaystyle xi xi is a Cox process directed by ηdisplaystyle eta eta , then ξdisplaystyle xi xi has got the Laplace transform


Lξ(f)=exp⁡(−∫1−exp⁡(−f(x))η(dx))displaystyle mathcal L_xi (f)=exp left(-int 1-exp(-f(x));eta (mathrm d x)right)displaystyle mathcal L_xi (f)=exp left(-int 1-exp(-f(x));eta (mathrm d x)right)

for any positive, measurable function fdisplaystyle ff.



See also


  • Poisson hidden Markov model

  • Doubly stochastic model


  • Inhomogeneous Poisson process, where λ(t) is restricted to a deterministic function

  • Ross's conjecture

  • Gaussian process

  • Mixed Poisson process


References


Notes


  1. ^ Cox, D. R. (1955). "Some Statistical Methods Connected with Series of Events". Journal of the Royal Statistical Society. 17 (2): 129–164. doi:10.2307/2983950. 


  2. ^ Krumin, M.; Shoham, S. (2009). "Generation of Spike Trains with Controlled Auto- and Cross-Correlation Functions". Neural Computation. 21 (6): 1642–1664. doi:10.1162/neco.2009.08-08-847. PMID 19191596. 


  3. ^ Lando, David (1998). "On cox processes and credit risky securities". Review of Derivatives Research. 2 (2–3): 99–120. doi:10.1007/BF01531332. 



Bibliography
  • Cox, D. R. and Isham, V. Point Processes, London: Chapman & Hall, 1980 ISBN 0-412-21910-7

  • Donald L. Snyder and Michael I. Miller Random Point Processes in Time and Space Springer-Verlag, 1991 ISBN 0-387-97577-2 (New York) ISBN 3-540-97577-2 (Berlin)






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