Acta Geodaetica et Cartographica Sinica >

2017 , Vol. 46 >Issue 7: 857 - 865

DOI: https://doi.org/10.11947/j.AGCS.2017.20160501

Non-negative Least Squares Variance Component Estimation of Partial EIV Model

  • WANG Leyang ,
  • WEN Guisen
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  • 1. Faculty of Geomatics, East China University of Technology, Nanchang 330013, China;
    2. Key Laboratory of Watershed Ecology and Geographical Environment Monitoring, NASG, Nanchang 330013, China;
    3. Key Laboratory for Digital Land and Resources of Jiangxi Province, Nanchang 330013, China

Received date: 2016-10-11

  Revised date: 2017-05-27

  Online published: 2017-07-25

Supported by

National Natural Science Foundation of China (Nos.41664001;41204003);Support Program for Outstanding Youth Talents in Jiangxi Province (No.20162BCB23050);National Key Research and Development Program(No.2016YFB0501405);Science and Technology Project of the Education Department of Jiangxi Province (No.GJJ150595);the Project of Key Laboratory for Digital Land and Resources of Jiangxi Province(No.DLLJ201705);Innovation Fund Designated for Graduate Students of ECUT(No.DHYC-2016005)

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Abstract

As an extended form of the errors-in-variables (EIV) model, and the weight matrix is easy to structure, the applicability is stronger when both non-random elements and random elements exist in the coefficient matrix. According to the inaccurate stochastic model in the Partial EIV model, the coefficient matrix and observation vector are used as a kind of data respectively. The least squares variance component estimation method based on Partial EIV model is used and the relevant calculated formulas and iterative algorithm are derived. Then the corresponded variance components are estimated. The non-negative least squares is used when the negative variance appears, then add constraint condition to correct the rand model, so the estimated parameters are more reasonable. The experiments show that the results obtained by the method of this paper and other methods are equivalent.

Key words： Partial EIV model; EIV model; least squares variance component estimation; non-negative least squares

Cite this article

WANG Leyang , WEN Guisen . Non-negative Least Squares Variance Component Estimation of Partial EIV Model[J]. Acta Geodaetica et Cartographica Sinica, 2017 , 46(7) : 857 -865 . DOI: 10.11947/j.AGCS.2017.20160501

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