Convolutional subordinator processes

March 8, 2021 — December 1, 2021

functional analysis
kernel tricks
machine learning
point processes
stochastic processes
time series
Figure 1

Defining stochastic processes by convolution of noise with smoothing kernels, where the driving noise is a Lévy 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,

1 References

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