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Scientia Silvae Sinicae ›› 2012, Vol. 48 ›› Issue (8): 54-61.doi: 10.11707/j.1001-7488.20120809

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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

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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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