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Register a new userNonparametric Bayesian estimation of multivariate Hawkes processes
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Added by
Vincent Rivoirard
Publication date
2018
fields
Mathematical Statistics
and research's language is
English
Authors
Sophie Donnet
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This paper studies nonparametric estimation of parameters of multivariate Hawkes processes. We consider the Bayesian setting and derive posterior concentration rates. First rates are derived for L1-metrics for stochastic intensities of the Hawkes process. We then deduce rates for the L1-norm of interactions functions of the process. Our results are exemplified by using priors based on piecewise constant functions, with regular or random partitions and priors based on mixtures of Betas distributions. Numerical illustrations are then proposed with in mind applications for inferring functional connec-tivity graphs of neurons.
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