Bayesian model predicts the aboveground biomass of Caragana microphylla in sandy lands better than OLS regression models |
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| Authors: | Yi Tang Arshad Ali Li-Huan Feng |
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| Affiliation: | 1. School of Life Science, Liaoning University, Shenyang 110036, Liaoning, China,;2. Department of Forest Resources Management, Collegeof Forestry, Nanjing Forestry University, Nanjing 210037, Jiangsu, China, ;3. Co-Innovation Center for Sustainable Forestry in SouthernChina, Nanjing Forestry University, Nanjing 210037, Jiangsu, China;Corresponding author. E-mail: arshadforester@njfu.edu.cn |
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| Abstract: | AimsIn forest ecosystems, different types of regression models have been frequently used for the estimation of aboveground biomass, where Ordinary Least Squares regression models (OLS) are the most common prediction models. Yet, the relative performance of Bayesian and OLS models in predicting aboveground biomass of shrubs, especially multi-stem shrubs, has relatively been less studied in forests. |
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| Keywords: | Bootstrap Caragana microphylla Horqin Sandy Land mean squared error Prior information |
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