Bayesian inference for partially observed multiplicative intensity processes

DOI10.1214/15-BA940zbMath1359.62354MaRDI QIDQ516447

Sophie Donnet, Judith Rousseau

Publication date: 14 March 2017

Published in: Bayesian Analysis (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ba/1425492492

zbMATH Keywords

Bayesian analysislatent variablescounting processmultiplicative intensity process

Mathematics Subject Classification ID

Non-Markovian processes: estimation (62M09) Censored data models (62N01) Bayesian inference (62F15) Applications of statistics in engineering and industry; control charts (62P30)

Cites Work

• Unnamed Item
• Adaptive estimation for Hawkes processes; application to genome analysis
• Applied nonparametric statistics in reliability
• On age-dependent branching processes with immigration
• Nonparametric inference for a family of counting processes
• Inference from iterative simulation using multiple sequences
• The Calculation of Posterior Distributions by Data Augmentation
• Particle filters for continuous-time jump models in tracking applications
• Computational Methods for Multiplicative Intensity Models Using Weighted Gamma Processes
• FADO: A Statistical Method to Detect Favored or Avoided Distances between Occurrences of Motifs using the Hawkes' Model
• Some theory for constructing general minimum lower order confounding designs
• Statistical models based on counting processes

This page was built for publication: Bayesian inference for partially observed multiplicative intensity processes