Variational inference for multiplicative intensity models

John W. LAU, Edward CRIPPS, Wendy HUI

Research output: Other PublicationsOther ArticleCommunication

Abstract

We extend variational inference approximation of probability density functions to multiplicative intensity functions. For Bayesian nonparametrics, this provides a computationally efficient alternative to the blocked Gibbs sampler described in Ishwaran and James (2004). Simulation results are presented to demonstrate performance.
Original languageEnglish
Pages108720
Volume161
Specialist publicationStatistics and Probability Letters
DOIs
Publication statusE-pub ahead of print - 4 Feb 2020

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Keywords

  • Variational inference
  • Multiplicative intensity
  • Bayesian nonparametrics

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