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林业科学 ›› 2012, Vol. 48 ›› Issue (8): 54-61.doi: 10.11707/j.1001-7488.20120809

• 论文 • 上一篇    下一篇

基于计数模型方法的林分枯损研究

张雄清1,2, 雷渊才1, 雷相东1, 陈永富1, 冯淼3   

  1. 1. 中国林业科学研究院资源信息研究所 北京 100091;2. 中国林业科学院林业研究所 北京 100091;3. 国家知识产权局专利局专利审查协作北京中心 北京 100083
  • 收稿日期:2011-09-07 修回日期:2011-11-27 出版日期:2012-08-25 发布日期:2012-08-25
  • 通讯作者: 雷渊才

Predicting Stand-Level Mortality with Count Data Models

Zhang Xiongqing1,2, Lei Yuancai1, Lei Xiangdong1, Chen Yongfu1, Feng Miao3   

  1. 1. Research Institute of Resources Information Techniques, CAF Beijing 100091;2. Research Institute of Forestry, CAF Beijing 100091;3. Patent Examination Cooperation Center of the Patent Office, SIPO Beijing 100083
  • Received:2011-09-07 Revised:2011-11-27 Online:2012-08-25 Published:2012-08-25

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。

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

Abstract:

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.

Key words: stand mortality, Poisson model, negative binomial model, zero-inflated model, Hurdle model

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