Predicting Stand-Level Mortality with Count Data Models
Stand mortality is a very important variable for describing the stand characters. Based on the stand mortality data from permanent plots of Larix spp. in Wangqing Forest Farm, Poisson model, negative binomial model, zero-inflated model and Hurdle model were introduced to model the stand mortality stems. And the best model was selected through AIC and Vuong test. Results showed that; Poisson model was not suitable for stand mortality, and negative was superior to the Poisson model. But both of them were not competent for the over-dispersion data of stand mortality. Zero-inflated model and Hurdle model were fitted into the data. Additionally, zero-inflated negative binomial model(ZINB) and Hurdle-NB model outperformed than other models. Furthermore, The Hurdle-NB model was a little better than ZINB model.
stand mortalityPoisson modelnegative binomial modelzero-inflated modelHurdle model
国家科技期刊平台
NSTL
万方数据
维普
