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

Journal of Forestry Research 2021年第4期32卷 1515-1533页

作者： Dechao Tian Huiquan Bi Xingji Jin Fengri Li Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education School of ForestryNortheast Forestry UniversityNo.26 Hexing RoadHarbin 150040People’s Republic of China Forest Science NSW Department of Primary Industries−ForestryLevel 1210 Valentine AveParramattaNSW 2150Australia School of Ecosystem and Forest Sciences The University of MelbourneParkvilleVIC 3010Australia

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 ***,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 *** 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 *** data from 170 plot measurements in even-aged Larix olgensis(***) plantations across a wide range of site qualities and with different abundances of woody weeds,*** 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 *** 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 *** parameter estimates had lower degrees of variability and correspondingly narrower confidence *** greater efficiency would naturally be conducive to making statistical *** 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 *** stochastic frontier estimation was also more objective because it did not involve the subjective selection of a particular value

关键词： Larix olgensis Normal-half normal distribution Site productivity woody weeds Sample size Quantile selection

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