Nonparametric measures of association between a spatial point process and a random set, with geological applications
By R. Foxall, Adrian Baddeley. 2002
56 citations recorded by the source corpus.
Subfields: Applied Mathematics, Artificial Intelligence, Environmental Engineering
View Paper: https://www.semanticscholar.org/paper/02d385180191719ff548447b303e4a7e8b4b0ffe
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
- Jesper Møller
- Adrian Baddeley
- M. V. Lieshout
- Rolf Turner
- Martin L. Hazelton
- Rasmus Waagepetersen
- Dominic Schuhmacher
- Andrew Hardegen
In Artificial Intelligence
- Rolf Turner
- Adrian Baddeley
- Martin L. Hazelton
- Jesper Møller
- M. V. Lieshout
- Mark Berman
- Andrew Hardegen
- Rohan Shah
In Environmental Engineering
- Jesper Møller
- Adrian Baddeley
- M. V. Lieshout
- Rolf Turner
- Dominic Schuhmacher
- Andrew Hardegen
- Robin K. Milne
- Martin L. Hazelton
Citations in the corpus
- A J-function for inhomogeneous point processes (2010, background): “For applications in agriculture, astronomy, forestry and geology, see [8, 13, 14, 15, 21, 24].”
- Spatial logistic regression and change-of-support in Poisson point processes (2010, methodology): “The Murchison data have been analysed by various methods [19, 33, 37, 46].”
- Residual analysis for spatial point processes (with discussion) (2005, background): “The influence of different parts of the data should also be investigated, since a comparison of the analyses has fortuitously identified some influential observations (Foxall and Baddeley (2002), section 5.3).”