Gaussian and Besov-Laplace priors yield minimax-optimal posterior contraction rates for nonparametric Bayesian intensity estimation in covariate-driven point processes under increasing domain asymptotics with ergodic covariates.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.ST 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Increasing domain asymptotics for covariate-based nonparametric Bayesian intensity estimation with Gaussian and Besov-Laplace priors
Gaussian and Besov-Laplace priors yield minimax-optimal posterior contraction rates for nonparametric Bayesian intensity estimation in covariate-driven point processes under increasing domain asymptotics with ergodic covariates.