Discussion of “New First-Order Approximate Precision Estimation Method for Parameters in an Errors-in-Variables Model” by Jie Han, Songlin Zhang, and Jingchang Li-Reference-Cited by-同舟云学术

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Discussion of “New First-Order Approximate Precision Estimation Method for Parameters in an Errors-in-Variables Model” by Jie Han, Songlin Zhang, and Jingchang Li

Published:2022-05 Issue:2 Volume:148 Page:
ISSN:0733-9453
Container-title:Journal of Surveying Engineering
language:en
Short-container-title:J. Surv. Eng.

Author:

Schaffrin Burkhard¹,Snow Kyle²^ORCID

Affiliation:

1. Professor Emeritus, Geodetic Science Program, School of Earth Sciences, Ohio State Univ., 275 Mendenhall Laboratory, 125 South Oval Mall, Columbus, OH 43210.

2. President, Polaris Geospatial Services, LLC, 7281 Park Bend Dr., Westerville, OH 43082; Adjunct Professor, Geodetic Science Program, School of Earth Sciences, Ohio State Univ., 275 Mendenhall Laboratory, 125 South Oval Mall, Columbus, OH 43210 (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29SU.1943-5428.0000383

Reference12 articles.

1. Weighted total least squares formulated by standard least squares theory

2. XI.The application of least squares

3. LXVII.On the application of least squares.—II

4. Iterative algorithm for weighted total least squares adjustment

5. Schaffrin B. 2015. “Adjusting the errors-in-variables model: Linearized least-squares vs. nonlinear total least-squares.” In Vol. 142 of Proc. VIII Hotine-Marussi Symp. on Mathematical Geodesy edited by N. Sneeuw P. Novák M. Crespi and F. Sansò 301–307. Cham Switzerland: Springer International.

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