In this work, we consider a hierarchical spatio-temporal model for particulate matter (PM) concentration in the North-Italian region Piemonte. The model involves a Gaussian Field (GF), affected by a measurement error, and a state process characterized by a first order autoregressive dynamic...

The second-order random walk (RW2) model is commonly used for smoothing data and for modelling response functions. It is computationally efficient due to the Markov properties of the joint (intrinsic) Gaussian density. For evenly spaced locations the RW2 model is well established, whereas for...

In this work we propose a model for the intensity of a space–time point process, specified by a sequence of spatial surfaces that evolve dynamically in time. This specification allows flexible structures for the components of the model, in order to handle temporal and spatial variations both...

<Para ID="Par1">Large spatial data sets require innovative techniques for computationally efficient statistical estimation. In this comment some aspects of local predictor selection are explored, with a view towards spatially coherent field prediction and uncertainty quantification. Copyright Sociedad de...</para>

type="main" xml:id="rssb12055-abs-0001" <title type="main">Summary</title> <p>In several areas of application ranging from brain imaging to astrophysics and geostatistics, an important statistical problem is to find regions where the process studied exceeds a certain level. Estimating such regions so that the probability for...</p>