Comparing composite likelihood methods based on pairs for spatial Gaussian random fields

@article{Bevilacqua2015ComparingCL,
  title={Comparing composite likelihood methods based on pairs for spatial Gaussian random fields},
  author={Moreno Bevilacqua and Carlo Gaetan},
  journal={Statistics and Computing},
  year={2015},
  volume={25},
  pages={877-892}
}
In the last years there has been a growing interest in proposing methods for estimating covariance functions for geostatistical data. Among these, maximum likelihood estimators have nice features when we deal with a Gaussian model. However maximum likelihood becomes impractical when the number of observations is very large. In this work we review some solutions and we contrast them in terms of loss of statistical efficiency and computational burden. Specifically we focus on three types of… 
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