Abstract
Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive or log linear random intensity functions. We moreover consider a new and flexible class of pair correlation function models given in terms of normal variance mixture covariance functions. The proposed methodology is applied to point pattern data sets of locations of tropical rain forest trees.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 119-137 |
| Number of pages | 19 |
| Journal | Scandinavian Journal of Statistics |
| Volume | 40 |
| Issue number | 1 |
| DOIs | |
| State | Published - Mar 2013 |
Fingerprint
Keywords
- Additive random intensity
- Composite likelihood
- Cox process
- Matérn covariance function
- Normal variance mixture
- Pair correlation function
- Variance component
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty
Cite this
Decomposition of Variance for Spatial Cox Processes. / Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus.
In: Scandinavian Journal of Statistics, Vol. 40, No. 1, 03.2013, p. 119-137.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Decomposition of Variance for Spatial Cox Processes
AU - Jalilian, Abdollah
AU - Guan, Yongtao
AU - Waagepetersen, Rasmus
PY - 2013/3
Y1 - 2013/3
N2 - Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive or log linear random intensity functions. We moreover consider a new and flexible class of pair correlation function models given in terms of normal variance mixture covariance functions. The proposed methodology is applied to point pattern data sets of locations of tropical rain forest trees.
AB - Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive or log linear random intensity functions. We moreover consider a new and flexible class of pair correlation function models given in terms of normal variance mixture covariance functions. The proposed methodology is applied to point pattern data sets of locations of tropical rain forest trees.
KW - Additive random intensity
KW - Composite likelihood
KW - Cox process
KW - Matérn covariance function
KW - Normal variance mixture
KW - Pair correlation function
KW - Variance component
UR - http://www.scopus.com/inward/record.url?scp=84873989331&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84873989331&partnerID=8YFLogxK
U2 - 10.1111/j.1467-9469.2012.00795.x
DO - 10.1111/j.1467-9469.2012.00795.x
M3 - Article
AN - SCOPUS:84873989331
VL - 40
SP - 119
EP - 137
JO - Scandinavian Journal of Statistics
JF - Scandinavian Journal of Statistics
SN - 0303-6898
IS - 1
ER -