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http://dx.doi.org/10.14578/jkfs.2015.104.1.111

Applicability Evaluation of a Mixed Model for the Analysis of Repeated Inventory Data : A Case Study on Quercus variabilis Stands in Gangwon Region  

Pyo, Jungkee (Forest Practice Research Center, Korea Forest Research Institute)
Lee, Sangtae (Forest Practice Research Center, Korea Forest Research Institute)
Seo, Kyungwon (Forest Practice Research Center, Korea Forest Research Institute)
Lee, Kyungjae (Forest Practice Research Center, Korea Forest Research Institute)
Publication Information
Journal of Korean Society of Forest Science / v.104, no.1, 2015 , pp. 111-116 More about this Journal
Abstract
The purpose of this study was to evaluate mixed model of dbh-height relation containing random effect. Data were obtained from a survey site for Quercus variabilis in Gangwon region and remeasured the same site after three years. The mixed model were used to fixed effect in the dbh-height relation for Quercus variabilis, with random effect representing correlation of survey period were obtained. To verify the evaluation of the model for random effect, the akaike information criterion (abbreviated as, AIC) was used to calculate the variance-covariance matrix, and residual of repeated data. The estimated variance-covariance matrix, and residual were -0.0291, 0.1007, respectively. The model with random effect (AIC = -215.5) has low AIC value, comparison with model with fixed effect (AIC = -154.4). It is for this reason that random effect associated with categorical data is used in the data fitting process, the model can be calibrated to fit repeated site by obtaining measurements. Therefore, the results of this study could be useful method for developing model using repeated measurement.
Keywords
calibration; mixed model; Quercus variabilis; random effect; variance-covariance matrix;
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