文献类型：期刊文献

中文题名：基于计数模型方法的林分枯损研究

英文题名：Predicting Stand-Level Mortality with Count Data Models

作者：张雄清[1,2] 雷渊才[1] 雷相东[1] 陈永富[1] 冯淼[3]

第一作者：张雄清

机构：[1]中国林业科学研究院资源信息研究所;[2]中国林业科学院林业研究所;[3]国家知识产权局专利局专利审查协作北京中心

年份：2012

卷号：48

期号：8

起止页码：54-61

中文期刊名：林业科学

外文期刊名：Scientia Silvae Sinicae

收录：CSTPCD;;Scopus;北大核心:【北大核心2011】；CSCD:【CSCD2011_2012】；

基金：林业公益性行业专项(201104006;201204510)

语种：中文

中文关键词：林分枯损;Poisson回归模型;负二项模型;零膨胀模型;Hurdle模型

外文关键词：stand mortality; Poisson model; negative binomial model; zero-inflated model; Hurdle model

分类号：S758.5

摘要：利用吉林省汪清林业局金沟岭林场落叶松林分连续观测数据,分别利用Poisson回归模型、负二项模型、零膨胀模型和Hurdle模型拟合林木枯损株数,并通过AIC值以及Vuong检验对这些模型进行详细分析比较。结果表明:Poisson回归模型不适用于模拟林木枯损株数,负二项回归模型相对于Poisson回归模型比较适用;但是对于零枯损过多的数据,这2类模型拟合效果较差。零膨胀模型和Hurdle模型对这类数据有很好的解决办法,其中,零膨胀负二项模型和Hurdle-NB模型拟合效果优于其他几种模型,且Hurdle-NB模型略好于零膨胀负二项模型。
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.