Dependent species sampling models for spatial density estimation

DOI10.1214/16-BA1006zbMath1384.62124WikidataQ110790850 ScholiaQ110790850MaRDI QIDQ1699661

Lorenzo Trippa, Fernando A. Quintana, Seongil Jo, Jaeyong Lee, Peter Mueller

Publication date: 23 February 2018

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

Full work available at URL: https://projecteuclid.org/euclid.ba/1462297334

zbMATH Keywords

conditional autoregressive modelclimate predictionspatial density estimationspecies sampling model

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15)

Related Items (7)

Bayesian temporal density estimation with autoregressive species sampling models ⋮ Spatial distribution of the earthquake in mainland China ⋮ Nonparametric Bayesian inference in applications ⋮ Discussion on the paper by Peter Müller, Fernando A. Quintana, and Garritt L. Page ⋮ Dependent Modeling of Temporal Sequences of Random Partitions ⋮ Sufficientness postulates for Gibbs-type priors and hierarchical generalizations ⋮ A Bayesian nonparametric spiked process prior for dynamic model selection

This page was built for publication: Dependent species sampling models for spatial density estimation