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Jackknife resampling parameter estimation method for weighted total least squares

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  • Leyang Wang
  • Fengbin Yu

Abstract

To make the result of weighted total least squares (WTLS) parameter estimation more accurate, the Jackknife method is used to resample the observed data and make full use of Jackknife samples for multiple calculations. Combining Jackknife-1 and Jackknife-d with the weighted total least squares, the calculation methods of Jackknife-1-WTLS and Jackknife-d-WTLS are proposed, and the value of d is further studied. Meanwhile, the two methods are applied to the linear regression model, the planar coordinate transformation model and big rotation angle’s 3 D coordinate transformation model. The results show that the proposed methods of Jackknife of weighted total least squares are more effective than least squares (LS), weighted total least squares and least squares resampling methods in improving the quality of parameter estimation, which verifies the validity and feasibility of the methods.

Suggested Citation

  • Leyang Wang & Fengbin Yu, 2020. "Jackknife resampling parameter estimation method for weighted total least squares," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 49(23), pages 5810-5828, December.
    • Handle: RePEc:taf:lstaxx:v:49:y:2020:i:23:p:5810-5828
    DOI: 10.1080/03610926.2019.1622725
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