GRASPA Conference Series

The GRASPA Conference Series is a key reference point for the scientific community engaged in developing and applying statistical methods for environmental data analysis. Promoted as part of the activities of the GRASPA group, the conference series brings together researchers, professionals, and early-career scholars interested in the challenges posed by the study of environmental systems, in a context marked by growing complexity, heterogeneous data availability, and the need for advanced analytical tools.

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GRASPA14
Proceedings of the METMA VII and GRASPA14 Conference. Torino (IT), 10-12 September 2014
GRASPA15
Proceedings of the GRASPA 2015 Conference. Bari (IT), 15-16 June 2015
GRASPA17
TIES - GRASPA 2017 on Climate and Environment: Book of Abstracts
GRASPA19
Proceedings of the GRASPA 2019 Conference. Pescara (IT), 15-16 July 2019
Spatial2 Conference 2011
Spatial Data Methods for Environmental and Ecological Processes. Foggia (IT), 1-2 September 2011

Ultimi inserimenti

Prior specification in one-factor mixed models applied to community ecology data

In community ecology studies the goal is to evaluate the effect of environmental covariates on a response variable while investigating the nature unobserved heterogeneity. We focus on onefactor mixed models in a Bayesian setting and introduce an intuitive Penalized Complexity (PC) prior to balance the variance components of the model. We start with the simple one-way anova and discuss extension to spatially structured residuals, following a Matern exponential covariance.

Induced earthquakes and the ETAS model

The epidemic type aftershock sequence (ETAS) model is widely used in the modelling of earthquake catalogues that include aftershocks. The model has be used successfully in describing tectonic seismicity where the usable catalogue sizes are large. The model is more difficult to apply to induced earthquakes, where catalogue sizes are typically much smaller and the seeding rate of main shocks cannot be assumed to be constant. In both cases, the parameters of the ETAS model are highly correlated ...

The preliminary study of the PM1 main components and of their seasonal variation using a linear parametric model

This study presents the mass concentration PM1(aerosol particles with an aerodynamic diameter below 1μm) together with sixteen related trace elements (i.e. Al, Ca, Cd, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Pb, S, Ti, Zn) measured during Summer and Winter periods in a characteristic anthropized area. Soil, Sulfate, total-metal-oxide (TMO) and the carbonaceous material (CM) masses were evaluated and considered as the main components of PM1. All variables were log transformed to smooth extreme reco...

A nonparametric spatio-temporal approach for multiple CUSUM charts of evapotranspiration

In recent years, the interest in natural resources management is increased. In this context, control charts, developed to monitor and maintain quality in industrial processes, are a useful monitoring and decision tool. In this paper, the behavior of an agro-metereological variable, named evapotranspiration, in an area of the northern part of Italy during a 25-year span (from 1992 to 2016) is studied through a nonparametric spatio-temporal geostatistical analysis and multiple CUSUM control ch...

Graphical model selection for air quality time series

We propose an objective Bayes approach based on graphical models for learning dependencies among multiple air quality time series within the framework of Vector Autoregressive (VAR) models. Using a fractional Bayes factor approach, we obtain the marginal likelihood in closed form and construct an MCMC algorithm for Bayesian graphical model determination with limited computational burden. We apply our method to study the interactions between four air pollutants over the municipality of Milan (...

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