Discussion of paper ``Nonparametric Bayesian inference in applications'' by Peter Müller, Fernando A. Quintana and Garritt L. Page
type: Item
instance of: scholarly article
title: Discussion of paper ``Nonparametric Bayesian inference in applications'' by Peter Müller, Fernando A. Quintana and Garritt L. Page
zbMATH Open document ID: 1396.62062
author: Athanasios Kottas
published in: Statistical Methods and Applications
publication date: 2018-08-21T00:00:00Z
Mathematics Subject Classification ID: 62G05
Mathematics Subject Classification ID: 62M30
Mathematics Subject Classification ID: 62F15
zbMATH DE Number: 6921679
zbMATH Keywords: Bayesian nonparametrics
zbMATH Keywords: Dirichlet process mixtures
zbMATH Keywords: integro-difference equation models
zbMATH Keywords: spatial Poisson processes
zbMATH Keywords: spatio-temporal modeling
describes a project that uses: spBayes
MaRDI profile type: Publication
full work available at URL: s10260-017-0398-7
OpenAlex ID: W2750699433
cites work: Q3190363
cites work: Spatial Poisson Regression for Health and Exposure Data Measured at Disparate Resolutions
cites work: Spatiotemporal prediction for log-Gaussian Cox processes
cites work: Space-time multi type log Gaussian Cox processes with a view to modelling weeds
cites work: Blur-generated non-separable space–time models
cites work: Q3058567
cites work: Bayesian Nonparametric Spatial Modeling With Dirichlet Process Mixing
cites work: Non-parametric Bayesian Estimation of a Spatial Poisson Intensity
cites work: Modeling a Poisson Forest in Variable Elevations: A Nonparametric Bayesian Approach
cites work: Q4510976
cites work: Computational Methods for Multiplicative Intensity Models Using Weighted Gamma Processes
cites work: Spatial mixture modelling for unobserved point processes: examples in immunofluorescence histology
cites work: A Bayesian hierarchical spatial point process model for multi-type neuroimaging meta-analysis
cites work: Bayesian Nonparametric Modeling for Comparison of Single-Neuron Firing Intensities
cites work: Bayesian mixture modeling for spatial Poisson process intensities, with applications to extreme value analysis
cites work: Modeling Disease Incidence Data with Spatial and Spatio Temporal Dirichlet Process Mixtures
cites work: Analysis of Minnesota colon and rectum cancer point patterns with spatial and nonspatial covariate information
cites work: Geometric stick-breaking processes for continuous-time Bayesian nonparametric modeling
cites work: Q4807532
cites work: Log Gaussian Cox Processes
cites work: Bayesian density estimation using bernstein polynomials
cites work: Bayesian non-parametric modeling for integro-difference equations
cites work: Flexible integro-difference equation modeling for spatio-temporal data
cites work: Stationary space-time Gaussian fields and their time autoregressive representation
cites work: Autoregressive Mixture Models for Dynamic Spatial Poisson Processes: Application to Tracking Intensity of Violent Crime
cites work: Mixture modeling for marked Poisson processes
cites work: A kernel-based spectral model for non-Gaussian spatio-temporal processes
cites work: Poisson/gamma random field models for spatial statistics
cites work: Modeling for seasonal marked point processes: an analysis of evolving hurricane occurrences
cites work: A Kernel-Based Spatio-Temporal Dynamical Model for Nowcasting Weather Radar Reflectivities
DOI: 10.1007/S10260-017-0398-7
description: scientific article; zbMATH DE number 6921679