Jackknife Method for Variance Components Estimation of Partial EIV Model
Publication: Journal of Surveying Engineering
Volume 146, Issue 4
Abstract
To further improve the quality of estimated values based on variance component estimation of the partial errors-in-variables (EIV) model, the jackknife resampling method is introduced in this paper. Focusing on the bias of variance component estimation and combining with the jackknife method, bias calculation and bias correction are performed. Two schemes for parameter estimation are identified, and detailed calculation steps and the whole procedure are given. The jackknife method for variance component estimation of the partial EIV model is evaluated. Meanwhile, these two new algorithms are applied to the straight-line fitting model, space-line fitting model, and plane coordinate transformation model. As shown in the experimental estimation results, both methods proposed can obtain more accurate estimated values than the traditional variance component estimation method, and the method with bias correction can obtain the optimal parameter estimates. The case studies demonstrate the effectiveness and reliability of the proposed procedure, which extends the theory of the jackknife method in parameter estimation and provides resampling insight to further investigate variance component estimation.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. (The types of the raw data, e.g., the straight-line fitting, space-line fitting, or plane coordinate transformation, can be provided as a MAT file.)
Acknowledgments
The authors are grateful to all the anonymous reviewers and editors for their careful review and valuable suggestions, which improved the quality of this paper. This research is supported by the National Natural Science Foundation of China (Nos. 41874001 and 41664001), Support Program for Outstanding Youth Talents in Jiangxi Province (No. 20162BCB23050), and National Key Research and Development Program (No. 2016YFB0501405).
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Published In
Journal of Surveying Engineering
Volume 146 • Issue 4 • November 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Apr 10, 2019
Accepted: Apr 10, 2020
Published online: Jun 26, 2020
Published in print: Nov 1, 2020
Discussion open until: Nov 26, 2020
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