Modelos gaussianos geoestatísticos espaço-temporais e aplicações / Space-time geostatisticals guassian models and aplications

AUTOR(ES)

Alexandre Sousa da Silva

DATA DE PUBLICAÇÃO

2007

RESUMO

The specification of space-time covariance functions is one of the possible strategies to model processes observed at different locations and time points. Such functions can define separable and non-separable processes and must attend the condition of positivedefiniteness. Among the strategies to obtain such valid functions are the ones suggested by Cressie and Huang (1999) and by Gneiting (2002). The former is based on the idea of obtaining valid functions in a space of increased dimension from valid functions on the primary dimension and requires operations in the frequency domain. Alternatively, the latter combines increasing monotone functions avoiding the inversion of spectral representations. There are still few reports of usage and comparisons of the strategies. This work follows Gneiting?s proposals with different values for the space-time interaction parameter. Models were applied for the analysis of two real data sets, one about fish stocks in the Portuguese coast and a second on soil water storage. The implementation on the R package RandomFields was used, with methodology and computational implementation being reviewed. For both case the separable model provided a satisfactory fit, based on maximum likelihood estimation.

ASSUNTO(S)

análise de covariância campos aleatórios random fields package estatística computacional sapce-time models geostatistic random fileds geoestatística simulação (estatística)

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