An analysis and comparison of predictors of random parameters demonstrated on planted loblolly pine diameter growth prediction

作者：Ni Chengcai; Nigh Gordon D^*

来源：Forestry, 2012, 85(2): 271-280.

DOI：10.1093/forestry/cps001

Non-linear mixed effects (NLME) models are now common in the forestry literature. The fixed effects parameters are estimated in the model fitting stage. For new individuals, the random effects parameters are predicted when the model is used to predict the response variable. Predicting both the random effects parameters and the response variable requires the underlying model to be linearized using a Taylor series expansion. This is done by expanding around the expected or predicted value of the random effects parameters. Whichever way is chosen, it should be consistent. However, mismatches between the predictors for the random effects and predictors for the future response are sometimes made in forestry growth and yield applications. We consider the implications of using mismatched predictors on a single-level NLME model. We analyzed and empirically compared a total of four combinations of two types of predictors for both the random effects and the response variable. Diameter at breast height was predicted for 140 loblolly pine trees using these four combinations of predictors. The predictors were evaluated with the mean squared error. Model accuracy was best when the predictors for the random effects and the response variables were based on the same expansion method.

• 出版日期2012-4
• 单位北华大学