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Abstract A nonparametric procedure to estimate the conditional probability that a nonstationary geostatistical process exceeds certain threshold value is proposed. The method consists of bootstrap algorithm combines simulation techniques with estimations trend and variability. local linear estimator, considering bandwidth matrix selected by takes spatial dependence into account, used trend. var...

[1] This study presents monthly CO2 fluxes from 1997 to 2001 at a 3.75 latitude 5 longitude resolution, inferred using a geostatistical inverse modeling approach. The approach focuses on quantifying the information content of measurements from the NOAA-ESRL cooperative air sampling network with regard to the global CO2 budget at different spatial and temporal scales. The geostatistical approach...

Genome-wide selection (GS) involves estimating breeding values using molecular markers spanning the entire genome. The success of GS approaches will depend crucially on the availability of efficient and easy-to-use computational tools. Therefore, approaches that can be implemented using mixed models hold particular promise and deserve detailed study. A particular class of mixed models suitable ...

Thin irregularly-shaped surfaces such as clay drapes often have a major control on flow and transport in heterogeneous porous media. Clay drapes are often complex curvilinear 3dimensional surfaces and display a very complex spatial distribution. Variogram-based stochastic approaches are often also not able to describe the spatial distribution of clay drapes since complex, curvilinear, continuou...

A typical model for geostatistical data when the observations are counts is the spatial generalised linear mixed model. We present a criterion for optimal sampling design under this framework which aims to minimise the error in the prediction of the underlying spatial random effects. The proposed criterion is derived by performing an asymptotic expansion to the conditional prediction variance. ...

LavaNet consists of a series of scripts written in Perl that give access to a neural network simulation environment inside a general mine planning package. LavaNet enables easy development of neural network training datasets using information from any of the data and model structures available, such as block models and drillhole databases. Neural networks can be trained inside the mine planning...

The impact of violence on the population's health profile in large Brazilian cities is a real concern and has been incorporated into the country's public health agenda. Although violent crimes affect the entire population, they are distributed unequally in the city. In this context, analytical tools to evaluate the risk and spatial distribution of homicide are important for surveillance and pre...