Monte Carlo Maximum Likelihood in Model-Based Geostatistics

By Ole F. Christensen. 2004

97 citations recorded by the source corpus.

Subfields: Applied Mathematics, Artificial Intelligence, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/df4b58dfe6c0bcb1e281109416fe17d8c6e885b4

How researchers see this paper

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

In Applied Mathematics

1. Jasper A. Vrugt
2. Budiman Minasny
3. Alex B. McBratney

In Artificial Intelligence

1. Alex B. McBratney
2. Budiman Minasny
3. Jasper A. Vrugt
4. Sabine Grunwald
5. Mojtaba Sadegh
6. Keith Beven
7. Patrick M. Reed
8. Jirka Šimůnek

In Environmental Engineering

1. Budiman Minasny
2. Alex B. McBratney
3. Jasper A. Vrugt
4. Sabine Grunwald
5. Tomislav Hengl
6. R. M. Lark
7. Oliver Watts
8. Gerard B. M. Heuvelink

Citations in the corpus

• Confronting uncertainty in model-based geostatistics using Markov Chain Monte Carlo simulation (2011, methodology): “Christensen (2004) demonstrated the use of MCMC for parameter estimation in model-based geostatistics, whereas Zhang (2002) used a MCMC approach to infer parameter distributions for spatial prediction of incidence rates of root disease.”