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- 2017
附有相对权比的PEIV模型总体最小二乘平差
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Abstract:
针对观测向量和系数矩阵权分配不合理、验前随机模型不准确的情况，以部分误差变量（partial errors-in-variables，PEIV）模型为基础，推导了附有相对权比的总体最小二乘平差算法；通过在平差准则中加入相对权比，自适应调整观测向量和系数矩阵随机元素对模型参数估计的贡献，给出了确定相对权比的验前单位权方差法和判别函数最小化迭代算法，该算法普遍适用于一般性的系数矩阵和权矩阵。通过直线拟合和坐标转换模拟算例的比较分析，发现当观测值和系数矩阵的验前单位权方差已知，且较准确时，验前单位权方差法确定相对权比和参数估计的效果较好；而以作为判别函数是判别函数最小化迭代算法中效果最好的
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