UCLA

Point process modeling is used to predict the conditional intensity of wildfire ignitions in California from 2008 to 2012. Weather variables from the closest station record are used as model covariates. To reduce computation requirements of maximum likelihood estimation, the Stoyan-Grabarnik statistic is employed. Models of various combinations and number of variables are examined, as well as models for specifically naturally occurring fires caused by lightning and fires caused by humans.