Application of least median of squared orthogonal distance(lmd)and lmd-based reweighted least squares (rls)methods on the stock-recruitment relationship

Wang Yan-jun; Liu Qun

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Application of least median of squared orthogonal distance(lmd)and lmd-based reweighted least squares (rls)methods on the stock-recruitment relationship

机译：最小二乘方正交距离（lmd）和基于lmd的加权最小二乘（rls）方法在股票招聘关系中的应用

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Analysis of stock-recruitment(SR)data is most often done by fitting various SR rela- tionship curves to the data. Fish population dynamics data often have stochastic variations and measure- ment errors, which usually result in a biased regression analysis. This paper presents a robust regression method, least median of squared orthogonal distance(LMD), which is insensitive to abnormal values in the dependent ad independent variables in a regression analysis.

机译：库存招聘（SR）数据的分析通常是通过将各种SR关系曲线拟合到数据来完成的。鱼类种群动态数据通常具有随机变化和测量误差，通常会导致偏差回归分析。本文提出了一种鲁棒的回归方法，即最小平方正交距离（LMD）的中值，该方法对回归分析中因变量和独立变量的异常值不敏感。

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《Chinese Journal of Oceanology and Limnology》 |1999年第1期|p.70-78|共9页
作者
Wang Yan-jun; Liu Qun;
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正文语种 eng
中图分类海洋学;
关键词
stock-recruitment relationship; least squares(LS); least median of squared orthogonal distance(LMD);

机译：库存-招聘关系;最小二乘法平方正交距离的最小中位数（LMD）;

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1. PERTURBATION THEORY FOR ORTHOGONAL PROJECTION METHODS WITH APPLICATIONS TO LEAST SQUARES AND TOTAL LEAST SQUARES [J] . Fierro RD., Bunch JR. Linear Algebra and its Applications . 1996,第0期

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2. Analytical quality assessment of iteratively reweighted least-squares (IRLS) method [J] . Jianfeng Guo Boletim de Ciências Geodésicas . 2014,第1期

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3. Investigation on the relationship between analytical precision and concentration with iteratively reweighted least-squares linear regression method [J] . Zhi Gao, Xiwen He, Guizhu Zhang, Talanta: The International Journal of Pure and Applied Analytical Chemistry . 1999,第2期

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4. Robust power control using iteratively reweighted least square (IRLS) for cognitive radio networks [C] . 12th IEEE International Conference on Communication Systems . 2010

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7. Perturbation theory for orthogonal projection methods with applications to least squares and total least squares [O] . Fierro Ricardo D., Bunch James R. 1996

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8. On the Theory and Application of Sum Composition of Latin Squares and Orthogonal Latin Squares. [R] . Hedayat, A., Seiden, E. 1972

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Application of least median of squared orthogonal distance(lmd)and lmd-based reweighted least squares (rls)methods on the stock-recruitment relationship

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