Convolutional subordinator processes



Defining stochastic processes by convolution of noise with smoothing kernels, where the driving noise is a LΓ©vy subordinator.

Why would we want this? One reason is that this gives us a way to create nonparametric distributions over measures.

A related but distinct technique is that we can create interesting Generalized GAmma convolution,

References

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Barndorff-Nielsen, Ole E., Jan Pedersen, and Ken-Iti Sato. 2001. β€œMultivariate Subordination, Self-Decomposability and Stability.” Advances in Applied Probability 33 (1): 160–87.
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