Stochastic frontiers or regression quantiles for estimating the self-thinning surface in higher dimensions?  

作　　者：Dechao Tian Huiquan Bi Xingji Jin Fengri Li 

机构地区：[1]Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education,School of Forestry,Northeast Forestry University,No.26 Hexing Road,Harbin 150040,People’s Republic of China [2]Forest Science,NSW Department of Primary Industries−Forestry,Level 12,10 Valentine Ave,Parramatta,NSW 2150,Australia [3]School of Ecosystem and Forest Sciences,The University of Melbourne,Parkville,VIC 3010,Australia

出　　处：《Journal of Forestry Research》2021年第4期1515-1533,共19页林业研究（英文版）

基　　金：funded by the National Key R&D Program of China (2017YFD0600402);Provincial Funding for National Key R&D Program of China in Heilongjiang Province(Project No.GX18B041);the Overseas Famous Scholar Program of the Ministry of Educatoin,China (Project No.MS2016DBLY018)。

摘　　要：Stochastic frontier analysis and quantile regression are the two econometric approaches that have been commonly adopted in the determination of the self-thinning boundary line or surface in two and higher dimensions since their introduction to the field some 20 years ago.However,the rational for using one method over the other has,in most cases,not been clearly explained perhaps due to a lack of adequate appreciation of differences between the two approaches for delineating the self-thinning surface.Without an adequate understanding of such differences,the most informative analysis may become a missed opportunity,leading to an inefficient use of data,weak statistical inferences and a failure to gain greater insight into the dynamics of plant populations and forest stands that would otherwise be obtained.Using data from 170 plot measurements in even-aged Larix olgensis(A.Henry) plantations across a wide range of site qualities and with different abundances of woody weeds,i.e.naturally regenerated non-crop species,in northeast China,this study compared the two methods in determining the self-thinning surface across eight sample sizes from 30 to 170 with an even interval of 20 observations and also over a range of quantiles through repeated random sampling and estimation.Across all sample sizes and over the quantile range of 0.90 ≤τ≤0.99,the normal-half normal stochastic frontier estimation proved to be superior to quantile regression in statistical efficiency.Its parameter estimates had lower degrees of variability and correspondingly narrower confidence intervals.This greater efficiency would naturally be conducive to making statistical inferences.The estimated self-thinning surface using all 170 observations enveloped about 96.5% of the data points,a degree of envelopment equivalent to a regression quantile estimation with aτ of 0.965.The stochastic frontier estimation was also more objective because it did not involve the subjective selection of a particular value of τ for the favoured self-thinning surfa

关 键 词：Larix olgensis Normal-half normal distribution Site productivity Woody weeds Sample size Quantile selection 

分 类 号：S718.5[农业科学—林学] O212.1[理学—概率论与数理统计]