A Fleming--Viot process and Bayesian nonparametrics
Stephen G. Walker, Spyridon J. Hatjispyros, Theodoros Nicoleris
Abstract
This paper provides a construction of a Fleming--Viot measure valued diffusion process, for which the transition function is known, by extending recent ideas of the Gibbs sampler based Markov processes. In particular, we concentrate on the Chapman--Kolmogorov consistency conditions which allows a simple derivation of such a Fleming--Viot process, once a key and apparently new combinatorial result for Pólya-urn sequences has been established.
Create a lesson
Related papers
Boolean Small-Ball Inequalities for Discrepancy Theory
Emrullah Akbas, Suvrit Sra
Markovian renormalisation for percolation in high-dimension: Semi-decidability of mean field behavior
Arthur Blanc-Renaudie
Point process convergence of large inradii of Poisson-Laguerre tessellations
Matthias Schulte, Martina Švarc Petráková
Interpolation of Gaussian Free Fields via Random Matrices
Gabriel Raposo
Almost-Uniform Bayesian Convergence to the Truth Is Not Characterized by Countable Additivity on Conditional Hitting Times
M. Ali Khan, Arthur Paul Pedersen, Maxwell B. Stinchcombe
The skeleton-blocks decomposition of Bienaymé trees, and applications to their local convergence
Marc Bernard, Robin Stephenson