A Comparison between Spatial Econometric Models and Random Forest for Modeling Fire Occurrence

A Comparison between Spatial Econometric Models and Random Forest for Modeling Fire Occurrence

Fire occurrence, which is examined in terms of fire density (number of fire/km2) in this paper, has a close correlation with multiple spatiotemporal factors that include environmental, physical, and other socioeconomic predictors. Spatial autocorrelation exists widely and should be considered seriously for modeling the occurrence of fire in urban areas. Therefore, spatial econometric models (SE...

Modeling Anthropogenic Fire Occurrence in the Boreal Forest of China Using Logistic Regression and Random Forests

Frequent and intense anthropogenic fires present meaningful challenges to forest management in the boreal forest of China. Understanding the underlying drivers of human-caused fire occurrence is crucial for making effective and scientifically-based forest fire management plans. In this study, we applied logistic regression (LR) and Random Forests (RF) to identify important biophysical and anthr...

Comparison and Disjoint-occurrence Inequalities for Random-cluster Models

Geoffrey Grimmett Abstra t. A principal technique for studying percolation, (ferromagnetic) Ising, Potts, and random-cluster models is the FKG inequality, which implies certain stochastic comparison inequalities for the associated probability measures. The first result of this paper is a new comparison inequality, proved using an argument developed in Refs. 2, 6, 14, and 21 in order to obtain s...

Smooth Coefficient Variation in Spatial Econometric Models: A Performance Comparison of Spatial STAR and GWR

Double Generalized Spatial Econometric Models

The authors offer a unified method extending traditional spatial dependence with normally distributed error terms to a new class of spatial models based on the biparametric exponential family of distributions. Joint modeling of the mean and variance (or precision) parameters is proposed in this family of distributions, including spatial correlation. The proposed models are applied for analyzing...