SUT法偏差改正的Partial EIV模型方差分量估计及其精度评定

由于部分变量误差（partial errors-in-variables，Partial EIV）模型方差分量估计精度评定理论不完善，将SUT采样法应用于Partial EIV模型的最小范数二次无偏估计（the minimum norm quadratic unbiased estimator, MINQUE），利用方差分量估计修正随机模型并以此作为先验信息对观测向量进行SUT法采样得到参数的加权均值和二阶精度信息。考虑到非线性模型的偏差，进行偏差改正，再通过SUT法对改正后的参数采样计算二阶精度信息。通过算例实验验证，结合SUT法和方差分量估计求解Partial EIV模型，能够有效地避免复杂的求导运算，并获得更为精确的参数估值和合理的二阶精度信息，表明偏差改正的必要性。

Partial EIV Model Variance Component Estimation and Accuracy Evaluation of SUT Method by Deviation Correction

The partial errors-in-variables model of variance component estimation precision evaluation theory needs improvement, so we apply the SUT sampling method to the minimum norm quadratic unbiased estimation of Partial EIV model. Using the variance component estimation modified stochastic model, we then use it as a priori information to obtain the weighted mean and second-order precision information by the SUT sampling method. Considering the deviation of the nonlinear model, the deviation correction is carried out, and the second-order precision information is calculated by the SUT method. An experiment shows that combining SUT method and variance component estimation to deal with Partial EIV model can effectively avoid complicated derivation operation, and gets more accurate parameter values and reasonable second-order accuracy information. It also shows the necessity of deviation correction.