Bayesian mixture modeling for spatial Poisson process intensities, with applications to extreme value analysis
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Publication:997304
DOI10.1016/j.jspi.2006.05.022zbMath1114.62100OpenAlexW1978537100MaRDI QIDQ997304
Athanasios Kottas, Bruno Sansó
Publication date: 23 July 2007
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jspi.2006.05.022
Bayesian nonparametricsDirichlet process mixture modelbivariate beta densityrandom intensity functionspatial point patterns
Inference from spatial processes (62M30) Nonparametric estimation (62G05) Bayesian inference (62F15) Statistics of extreme values; tail inference (62G32)
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Cites Work
- On a class of Bayesian nonparametric estimates: I. Density estimates
- Bayes methods for a symmetric unimodal density and its mode
- Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems
- Ferguson distributions via Polya urn schemes
- Extreme value analysis of environmental time series: an application to trend detection in ground-level ozone. With comments and a rejoinder by the author
- Nonparametric Bayesian data analysis
- Nonparametric hierarchical Bayes via sequential imputations
- Prior distributions on spaces of probability measures
- Bayesian analysis of extreme values by mixture modelling
- A Bayesian analysis of some nonparametric problems
- Nonparametric Bayesian survival analysis using mixtures of Weibull distributions
- Space-time Multi Type Log Gaussian Cox Processes with a View to Modelling Weeds
- Spatiotemporal Prediction for Log-Gaussian Cox Processes
- Analysing Data from Hormone-Receptor Assays
- Poisson/gamma random field models for spatial statistics
- Non-parametric Bayesian Estimation of a Spatial Poisson Intensity
- Log Gaussian Cox Processes
- Spatio-temporal Modelling of Weeds by Shot-noiseG Cox processes
- Shot noise Cox processes
- Spatial Poisson Regression for Health and Exposure Data Measured at Disparate Resolutions
- Modeling a Poisson Forest in Variable Elevations: A Nonparametric Bayesian Approach
- Generalised shot noise Cox processes
- An Introduction to the Theory of Point Processes
- Bayesian Density Estimation and Inference Using Mixtures
- Generalized Gamma measures and shot-noise Cox processes
- Computational Methods for Multiplicative Intensity Models Using Weighted Gamma Processes
- The two-dimensional Poisson process and extremal processes
- Efficient MCMC Schemes for Robust Model Extensions Using Encompassing Dirichlet Process Mixture Models
- An introduction to statistical modeling of extreme values
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