R package. CompRandFld: Composite-Likelihood Based Analysis of Random Fields. A set of procedures for the analysis of Random Fields using likelihood and non-standard likelihood methods is provided. Spatial analysis often involves dealing with large dataset. Therefore even simple studies may be too computationally demanding. Composite likelihood inference is emerging as a useful tool for mitigating such computational problems. This methodology shows satisfactory results when compared with other techniques such as the tapering method. Moreover, composite likelihood (and related quantities) have some useful properties similar to those of the standard likelihood.
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Bevilacqua, M.; Fassò, A.; Gaetan, C.; Porcu, E.; Velandia, D.: Covariance tapering for multivariate Gaussian random fields estimation (2016)
- Bevilacqua, Moreno; Alegria, Alfredo; Velandia, Daira; Porcu, Emilio: Composite likelihood inference for multivariate Gaussian random fields (2016)
- Bevilacqua, Moreno; Gaetan, Carlo: Comparing composite likelihood methods based on pairs for spatial Gaussian random fields (2015)
- Bacro, Jean-Noel; Gaetan, Carlo: Estimation of spatial max-stable models using threshold exceedances (2014)