TY - JOUR
T1 - Structured Spatio-temporal shot-noise Cox point process models, with a view to modelling forest fires
AU - Møller, Jesper
AU - Diaz-Avalos, Carlos
PY - 2010
Y1 - 2010
N2 - Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable for statistical analysis, using spatio-temporal versions of intensity and inhomogeneous K-functions, quick estimation procedures based on composite likelihoods and minimum contrast estimation, and easy simulation techniques. These advantages are demonstrated in connection with the analysis of a relatively large data set consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent.
AB - Spatio-temporal Cox point process models with a multiplicative structure for the driving random intensity, incorporating covariate information into temporal and spatial components, and with a residual term modelled by a shot-noise process, are considered. Such models are flexible and tractable for statistical analysis, using spatio-temporal versions of intensity and inhomogeneous K-functions, quick estimation procedures based on composite likelihoods and minimum contrast estimation, and easy simulation techniques. These advantages are demonstrated in connection with the analysis of a relatively large data set consisting of 2796 days and 5834 spatial locations of fires. The model is compared with a spatio-temporal log-Gaussian Cox point process model, and likelihood-based methods are discussed to some extent.
U2 - 10.1111/j.1467-9469.2009.00670.x
DO - 10.1111/j.1467-9469.2009.00670.x
M3 - Journal article
SN - 0303-6898
VL - 37
SP - 2
EP - 25
JO - Scandinavian Journal of Statistics
JF - Scandinavian Journal of Statistics
IS - 1
ER -