• Publications
  • Influence
Objective Bayesian Analysis of Spatially Correlated Data
Spatially varying phenomena are often modeled using Gaussian random fields, specified by their mean function and covariance function. The spatial correlation structure of these models is commonlyExpand
  • 457
  • 56
  • PDF
Paralytic shellfish poisoning: clinical and electrophysiological observations
Abstract In paralytic shellfish poisoning a mollusc contaminated with a toxin (saxitoxin) causes a potentially lethal disease, clinically characterised by gastrointestinal and neurological symptoms,Expand
  • 37
  • 2
Luminescence dating of quaternary deposits in geology in Brazil.
In the present work, systematic dating by luminescence methods has been done on 50 Quaternary geological samples within the study area of São Paulo State, Brazil. Bleaching experiments showed thatExpand
  • 14
  • PDF
Maximum likelihood and restricted maximum likelihood estimation for a class of Gaussian Markov random fields
This work describes a Gaussian Markov random field model that includes several previously proposed models, and studies properties of its maximum likelihood (ML) and restricted maximum likelihoodExpand
  • 9
A note on a non-stationary point source spatial model
A point source, non-stationary covariance structure model is proposed, having only one additional parameter over a standard, stationary covariance structure, spatial model. Additionally, the proposedExpand
  • 4
Bayesian Inference and Prediction of Gaussian Random Fields Based on Censored Data
This work develops a Bayesian approach to perform inference and prediction in Gaussian random fields based on spatial censored data. These type of data occur often in the earth sciences due either toExpand
A simple model for spatial rainfall fields
Spatial rainfall amounts accumulated over short to medium periods of time, say a few days, tend to have a probabilistic structure with very distinctive features. Some of these that are speciallyExpand