Non-Gaussian Bayesian Geostatistical Modeling

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On spatial skew‐Gaussian processes and applications (2009, background): “Recently, Palacios and Steel (2006) proposed Gaussian-logGaussian (GLG) model by using scale mixing of Gaussian processes.”
Space‐time modelling of trends in temperature series (2011, background): “See Baillie et al. (1996) and Giraitis et al. (2000) for the definition of different long memory volatility time series processes and Palacios and Steel (2006) and Huang et al. (2011) for models for spatial processes.”
Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors (2014, background): “ of exibility without sacricing its simple structure. We stress that the principles provided in this paper do not absolve modellers of the responsibility to check their suitability (see, for example,Palacios and Steel, 2006, who argued that the principles underlying the reference prior approach are ”
Generalized spatial dirichlet process models (2007, background): “…variability is attributable to more than one latent process, so that, for example, a mixture of Gaussian processes might be more appropriate; see Brown et al. (2003) for a recent example or Palacios & Steel (2006) for the development of a class of models able to cope with heavy tail behaviour.”