Bias-corrected variance components estimation of Partial EIV model

doi:10.11947/j.AGCS.2019.20170693

Abstract

Abstract: Considering the methods of variance components estimation (VCE) in Partial errors-in-variables (Partial EIV) model have not considered the effect of the bias of parameter estimates, the formulas of bias and second-order covariance matrix of parameter estimates are presented with the Partial EIV model regarded as a non-linear function and the parameter estimates after bias-correct are calculated. Combining the VCE method, the matrix variable influenced by the parameter estimates is updated, and an iterative method of variance components estimation based on bias-correct is given. The experiments show that the reasonable parameter estimates and its second-order approximate covariance results are affected by the bias of parameter estimates. The reasonable parameter estimates and variance components estimates can be obtained through the bias-correct and the second-order information obtained can reasonably evaluate precision of parameter estimates.

Key words: Partial EIV model, non-linear, bias correction, variance components estimation

CLC Number:

P207

WANG Leyang, WEN Guisen. Bias-corrected variance components estimation of Partial EIV model[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(4): 412-421.

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