摘要
针对相关观测的部分变量误差(partial errors-invariables,PEIV)模型并考虑平差时随机模型的不准确,将函数模型作为非线性最小二乘并进行泰勒展开迭代求解,结合最小二乘方差分量估计方法,推导了相关观测PEIV模型的最小二乘方差分量估计公式,并给出了相应的迭代算法,通过公式推导得到相关观测PEIV模型的最小二乘方差分量估计与已有方差分量估计方法等价。实验结果表明,相关观测下对随机模型进行修正的方差分量估计方法可以得到更加合理的参数估值,该方法更具一般性。
Considering the partial errors-in-variables(PEIV)model with correlated observations and the inaccuracy of the stochastic model,the method of Taylor expansion is used when the PEIV model was regarded as a non-linear least squares.The formulas of least square variance components estimation of PEIV model with correlated observations are derived and the iterative algorithm is presented in this paper.The equivalence between the least square variance components estimation of PEIV model with correlated observations and the existed variance components estimation method has been proved.Experiments show that the variance components estimation method can obtain more reasonable parameter estimation through correcting the stochastic model under the correlated observations,the method of this paper is more general than the exist methods.
引文
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