最小一乘估计快速算法

Quick Algorithm for Least Absolute Deviation Estimator

  • 摘要: 最小二乘估计容易受奇异点的影响, 最小一乘估计是稳健估计, 可以很好地克服这个缺陷, 但计算困难. 基于非退化模型假设下的稳定极点理论, 本文找到了快速准确求解最小一乘估计的迭代算法, 并给出算法的计算过程及与线性规划求解的比较, 较好地解决了最小一乘估计计算难的问题, 使其成为有效的参数估计方法.

     

    Abstract: Least square estimator (LSE) is disturbed easily by singular point; least absolute deviation estimator (LADE) can overcome the influence of singular point, but it is difficult in calculation. A convergent algorithm for LADE based on the stable pole theorem of LADE under non-degenerate model is obtained in this paper. The progress of algorithm and comparison of linear programming are derived. Further this algorithm makes LADE more effective.

     

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