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논문검색

Probability Estimation of Snow Damage on Sugi(Cryptomeria japonica) Forest Stands by Logistic Regression Model in Toyama Prefecture, Japan

초록

영어

In this paper, we apply a logistic regression model to the data of snow damage on sugi (Cryptomeria japonica) occurred in Toyama prefecture (in Japan) in 2004 for estimating the risk probability. In order to specify the factors effecting snow damage, we apply a model selection procedure determining optimal subset of explanatory variables. In this process we consider the following 3 information criteria, 1) Akaike’'s information criterion, 2) Baysian information criterion, 3) Bias-corrected Akaike’'s information criterion. For the selected variables, we give a proper interpretation from the viewpoint of natural disaster.

목차

ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED

저자정보

  • Ken-ichi Kamo Department of Liberal Arts and Sciences, Sapporo Medical University
  • Hirokazu Yanagihara Department of Mathematics, Graduate School of Science, Hiroshima University
  • Akio Kato Toyama Agriculture, Forest Research Center
  • Atsushi Yoshimoto 4Institute of Statistical Mathematics

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