Estimating Space and Space-Time Covariance Functions for Large Data Sets: A Weighted Composite Likelihood Approach

By Moreno Bevilacqua, Carlo Gaetan, Jorge Mateu, Emilio Porcu. 2012

178 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Economics and Econometrics, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/f83111ee082e17117c509b24f9733c10e674a211

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Raphaël Huser
2. Simone A. Padoan
3. Joseph Guinness
4. Mathieu Ribatet
5. Matthias Katzfuss
6. A. C. Davison

In Economics and Econometrics

1. Raphaël Huser
2. A. C. Davison
3. Mathieu Ribatet
4. Simone A. Padoan
5. Joseph Guinness
6. Matthias Katzfuss
7. Emeric Thibaud
8. Thomas Opitz

In Environmental Engineering

1. Raphaël Huser
2. A. C. Davison
3. Mathieu Ribatet
4. Thomas Opitz
5. Simone A. Padoan
6. Joseph Guinness
7. Matthias Katzfuss
8. Emeric Thibaud

Citations in the corpus

• Disaggregating daily precipitations into hourly values with a transformed censored latent Gaussian process (2015, unknown): “We will follow Bevilacqua et al. (2012) for selecting the adequate value D by seeking the value The matrix G D is the Godambe information matrix associated to the WPL in Eq.”
• Space–time modelling of extreme events (2012, background): “Bevilacqua et al. (2012) discussed related issues in the context of Gaussian random fields.”
• A General Framework for Vecchia Approximations of Gaussian Processes (2017, background): “More general composite likelihood approaches (e.g., Bevilacqua et al., 2012; Eidsvik et al., 2014) also assume conditional independence and result in unbiased estimating equations, but they do not respect a particular ordering and thus can lead to improper joint distributions.”
• Statistical Modeling of Spatial Extremes (2012, background): “…burden of the composite likelihood could be the downweighting or exclusion of likelihood contributions from sites very far apart, as suggested by Bevilacqua et al. (2012) and Padoan, Ribatet and Sisson (2010); in the context of time series, including unnecessary pairs can degrade inference…”
• Statistical Modelling of Spatial Extremes (2012, background): “Another way to improve statistical efficiency while reducing the computational burden of composite likelihood could be the downweighting or exclusion of likelihood contributions from sites very far apart, as suggested by Bevilacqua et al. (2011) and Padoan et al.”