Nearest neighbors weighted composite likelihood based on pairs for (non-)Gaussian massive spatial data with an application to Tukey-hh random fields estimation
Authors:
- Christian Caamaño-CarrilloChristian Caamaño-Carrillo
- Moreno BevilacquaMBMoreno Bevilacqua
- Cristian LópezCLCristian López
- Víctor Morales-OñateVMVíctor Morales-Oñate
- 10 November 2023
- journal article
- research article
- Published by Elsevier in Computational Statistics & Data Analysis
- Vol. 191
Abstract
No abstract availableKeywords
All Related Versions
Funding Information
- ANID
This publication has 57 references indexed in Scilit:
- Estimation and Prediction in Spatial Models With Block Composite LikelihoodsJournal of Computational and Graphical Statistics, 2014
- Gaussian copula marginal regressionElectronic Journal of Statistics, 2012
- Copula-based geostatistical modeling of continuous and discrete data including covariatesStochastic Environmental Research and Risk Assessment, 2009
- On spatial skew‐Gaussian processes and applicationsEnvironmetrics, 2009
- Covariance Tapering for Likelihood-Based Estimation in Large Spatial Data SetsJournal of the American Statistical Association, 2008
- Gaussian Predictive Process Models for Large Spatial Data SetsJournal of the Royal Statistical Society Series B: Statistical Methodology, 2008
- Copula‐based geostatistical models for groundwater quality parametersWater Resources Research, 2006
- Covariance Tapering for Interpolation of Large Spatial DatasetsJournal of Computational and Graphical Statistics, 2006
- A Latent Gaussian Markov Random-Field Model for Spatiotemporal Rainfall DisaggregationJournal of the Royal Statistical Society Series C: Applied Statistics, 2003
- A Composite Likelihood Approach to Binary Spatial DataJournal of the American Statistical Association, 1998