Due to the existence of a constant sum of constraints, the geochemical data is presented as the compositional data that has a closed number system. A closed number system is a dataset that includes several variables. The summation value of variables is constant, being equal to one. By calculating the correlation coefficient of a closed number system and comparing it with an open number system, ...

Seismic inversion is a method that extracts acoustic impedance data from the seismic traces. Source wavelets are band-limited, and thus seismic traces do not contain low and high frequency information. Therefore, there is a serious problem when the deterministic seismic inversion is applied to real data and the result of deterministic inversion is smooth. Low frequency component is obtained fro...

We present new spatio-temporal geostatistical modelling and interpolation capabilities of the R package gstat. Various spatio-temporal covariance models have been implemented, such as the separable, product-sum, metric and sum-metric models. In a real-world application we compare spatio-temporal interpolations using these models with a purely spatial kriging approach. The target variable of the...

In this paper we show the usage of robust multivariate statistical methods in geostatistics. A usual procedure to estimate the values of variables (e.g. geochemical variables) measured at certain points of a region is to apply geostatistical methods like Krige estimation (based on the estimation of variograms). Here we emphasize robust principal component and factor analysis for the preliminary...

Introduction There are different national approaches to the analysis, processing and presentation of indoor radon data. Some of them were presented at the international workshop in Lausanne (IGAR 2005). EU radon surveys were compiled in JRC Ispra summary report (Dubois 2005). Swiss experience on indoor radon data treatment and mapping using geostatistical approaches (both interpolations and sim...

Geostatistics of extreme values makes it possible to model the asymptotic behavior random phenomena that depend on time or space. In this paper, we propose new models extremal coefficient a stationary field where cumulative distribution is associated with multivariate copula. More precisely, some extensions extremogram and these derivatives are built in spatial framework. Moreover, both two geo...

This paper applies statistical and geostatistical procedures to a soil chronosequence on the Ž . terraces of the Henares River NE Madrid to analyse the spatial distribution of several soil properties and use the contribution of geostatistics to establishing a landscape evolution model of the area. Particle-size distribution, pH, calcium carbonate and organic carbon were analysed. Statistical pr...

Geostatistical modeling of reservoir properties is common in the assessment of expected reservoir flow. Typically, static properties such as porosity, saturation and permeability are modeled with geostatistical techniques to quantify the level of uncertainty in reservoir characterization. Lately, practitioners have become concerned that purely statistical techniques do not sufficiently integrat...

Abstract This article describes two R packages for probabilistic weather forecasting, ensembleBMA, which offers ensemble postprocessing via Bayesian model averaging (BMA), and ProbForecastGOP, which implements the geostatistical output perturbation (GOP) method. BMA forecasting models use mixture distributions, in which each component corresponds to an ensemble member, and the form of the compo...