Bayesian parameter inference for partially observed stopped processes

  title={Bayesian parameter inference for partially observed stopped processes},
  author={Ajay Jasra and Nikolas Kantas and Adam Persing},
  journal={Statistics and Computing},
BY AJAY JASRA, NIKOLAS KANTAS & ADAM PERSING 1Department of Statistics & Applied Probability, National University of Singapore, Singapore, 117546, SG. E-Mail: 2Department of Statistical Science, University College London, London, W1CE 6BT, UK. E-Mail: 3Department of Mathematics, Imperial College London, London, SW7 2AZ, UK. E-Mail: 

From This Paper

Figures and tables from this paper.
4 Citations
32 References
Similar Papers


Publications referenced by this paper.
Showing 1-10 of 32 references

Feynman-Kac Formulae: Genealogical and Interacting Particle Systems with Applications

  • P. Del Moral
  • 2004
Highly Influential
4 Excerpts

Importance sampling on coalescent histories. II: Subdivided population models

  • M. De Iorio, R. C. Griffiths
  • Adv. Appl. Probab
  • 2004
Highly Influential
4 Excerpts

SMC2: A sequential Monte Carlo algorithm with particle Markov chain Monte Carlo updates

  • N. Chopin, P. Jacob, O. Papaspiliopoulos
  • Technical Report, ENSAE,
  • 2011
1 Excerpt

Discussion of Particle Markov chain Monte Carlo methods

  • N. Whiteley
  • J. R. Statist. Soc. Ser. B,
  • 2010
1 Excerpt

Estimation in discretely observed Markov processes killed at a threshold

  • E. Bibbona, S. Ditlevsen
  • Technical Report,
  • 2010
2 Excerpts

Similar Papers

Loading similar papers…