Developing an Improved Parameter Estimation Method for the Segmented Taper Equation through Combination of Constrained Two-Dimensional Optimum Seeking and Least Square Regression
Pang, Lifeng1; Ma, Yongpeng2; Sharma, Ram P.3; Rice, Shawn4; Song, Xinyu5; Fu, Liyong1,6
2016-09-01
发表期刊FORESTS
卷号7期号:9页码:00194
摘要The segmented taper equation has great flexibility and is widely applied in exiting taper systems. The unconstrained least square regression (ULSR) was generally used to estimate parameters in previous applications of the segmented taper equations. The joint point parameters estimated with ULSR may fall outside the feasible region, which leads to the results of the segmented taper equation being uncertain and meaningless. In this study, a combined method of constrained two-dimensional optimum seeking and least square regression (CTOS & LSR) was proposed as an improved method to estimate the parameters in the segmented taper equation. The CTOS & LSR was compared with ULSR for both individual tree-level equation and the population average-level equation using data from three tropical precious tree species (Castanopsis hystrix, Erythrophleum fordii, and Tectona grandis) in the southwest of China. The differences between CTOS & LSR and ULSR were found to be significant. The segmented taper equation estimated using CTOS & LSR resulted in not only increased prediction accuracy, but also guaranteed the parameter estimates in a more meaningful way. It is thus recommended that the combined method of constrained two-dimensional optimum seeking and least square regression should be a preferred choice for this application. The computation procedures required for this method is presented in the article.
关键词Segmented Taper Equation Unconstrained Least Square Regression Constrained Two-dimensional Optimum Seeking Parameter Estimation Precious Tree Species
DOI10.3390/f7090194
收录类别SCI
语种英语
WOS记录号WOS:000385428900012
引用统计
文献类型期刊论文
条目标识符http://ir.kib.ac.cn/handle/151853/33644
专题中国科学院东亚植物多样性与生物地理学重点实验室
作者单位1.Chinese Acad Forestry, Res Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China
2.Chinese Acad Sci, Kunming Inst Bot, Key Lab Plant Divers & Biogeog East Asia, Kunming 650201, Yunnan, Peoples R China
3.Czech Univ Life Sci Prague, Fac Forestry & Wood Sci, Prague 6, Czech Republic
4.Penn State Coll Med, Penn State Hershey Canc Inst, Hershey, PA 17033 USA
5.Xinyang Normal Univ, Coll Comp & Informat Tech, Xinyang 464000, Henan, Peoples R China
6.Penn State Univ, Ctr Stat Genet, Loc T3436,Mailcode CH69,500 Univ Dr, Hershey, PA 17033 USA
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Pang, Lifeng,Ma, Yongpeng,Sharma, Ram P.,et al. Developing an Improved Parameter Estimation Method for the Segmented Taper Equation through Combination of Constrained Two-Dimensional Optimum Seeking and Least Square Regression[J]. FORESTS,2016,7(9):00194.
APA Pang, Lifeng,Ma, Yongpeng,Sharma, Ram P.,Rice, Shawn,Song, Xinyu,&Fu, Liyong.(2016).Developing an Improved Parameter Estimation Method for the Segmented Taper Equation through Combination of Constrained Two-Dimensional Optimum Seeking and Least Square Regression.FORESTS,7(9),00194.
MLA Pang, Lifeng,et al."Developing an Improved Parameter Estimation Method for the Segmented Taper Equation through Combination of Constrained Two-Dimensional Optimum Seeking and Least Square Regression".FORESTS 7.9(2016):00194.
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