arXiv · 1202.0264
Faa di Bruno's formula for Gateaux differentials and interacting stochastic population processes
Abstract
The problem of estimating interacting systems of multiple objects is important to a number of different fields of mathematics, physics, and engineering. Drawing from a range of disciplines, including statistical physics, variational calculus, point process theory, and statistical sensor fusion, we develop a unified probabilistic framework for modelling systems of this nature. In order to do this, we derive a new result in variational calculus, Faa di Bruno's formula for Gateaux differentials. Using this result, we derive the Chapman-Kolmogorov equation and Bayes' rule for stochastic population processes with interactions and hierarchies. We illustrate the general approach through case studies in multi-target tracking, branching processes and renormalization.
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Daniel E. Clark, Jeremie Houssineau. 2012-09-06. Faa di Bruno's formula for Gateaux differentials and interacting stochastic population processes. https://arxiv.org/abs/1202.0264
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