文献类型：期刊文献

英文题名：Developing an Improved Parameter Estimation Method for the Segmented Taper Equation through Combination of Constrained Two-Dimensional Optimum Seeking and Least Square Regression

作者：Pang, Lifeng[1] Ma, Yongpeng[2] Sharma, Ram P.[3] Rice, Shawn[4] Song, Xinyu[5] Fu, Liyong[1,6]

第一作者：庞丽峰

通信作者：Fu, LY[1];Fu, LY[2]

机构：[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

年份：2016

卷号：7

期号：9

外文期刊名：FORESTS

收录：;EI(收录号：20164202912272);Scopus(收录号：2-s2.0-84990937782);WOS:【SCI-EXPANDED(收录号:WOS:000385428900012)】；

基金：We are grateful to Shouzheng Tang, Yuancai Lei, Yuanchang Lu and other researchers in the Chinese Academy of Forestry for their valuable suggestions on this study. We also thank the Experimental Center of Tropical Forestry, Chinese Academy of Forestry Sciences for providing friendly help during the data collection. Financial support for this study was provided by the National High-tech R & D Program of China (863 Program) (No. 2012AA102002), the Basic Scientific Research Business of Central Public Research Institutes (No. IFRIT2013), the Forestry Public Welfare Scientific Research Project of China (No. 201404417) and the National Natural Science Foundations of China (Nos. 31300534, 31570628, 31470641).

语种：英文

外文关键词：segmented taper equation; unconstrained least square regression; constrained two-dimensional optimum seeking; parameter estimation; precious tree species

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.