New First-Order Approximate Precision Estimation Method for Parameters in an Errors-in-Variables Model-Reference-Cited by-同舟云学术

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New First-Order Approximate Precision Estimation Method for Parameters in an Errors-in-Variables Model

Published:2021-02 Issue:1 Volume:147 Page:04020023
ISSN:0733-9453
Container-title:Journal of Surveying Engineering
language:en
Short-container-title:J. Surv. Eng.

Author:

Han Jie¹^ORCID,Zhang Songlin²,Li Jingchang³^ORCID

Affiliation:

1. Ph.D. Student, College of Surveying and Geo-Infomatics, Tongji Univ., Shanghai 20092, China. ORCID: .

2. Professor, College of Surveying and Geo-Infomatics, Tongji Univ., Shanghai 20092, China (corresponding author).

3. Master’s Student, College of Surveying and Geo-Infomatics, Tongji Univ., Shanghai 20092, China. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29SU.1943-5428.0000335

Reference42 articles.

1. Total Least Squares Solution of Coordinate Transformation

2. Parameter estimation in 3D affine and similarity transformation: implementation of variance component estimation

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

4. Data-snooping procedure applied to errors-in-variables models

5. Weighted total least squares applied to mixed observation model

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Comparison of Posterior Precision Estimation Methods of Weighted Total Least-Squares Solution for Errors-in-Variables Model;Journal of Surveying Engineering;2024-11

2. New second order approximation method for posterior precision evaluation of weighted total least squares estimates with analytical expression;Communications in Statistics - Simulation and Computation;2023-07-20

3. Complete q-th moment convergence for the maximum of partial sums of m-negatively associated random variables and its application to the EV regression model^*;Stochastic Models;2022-09-16

4. A SCR method for uncertainty estimation in geodesy non-linear error propagation: Comparisons and applications;Geodesy and Geodynamics;2022-07

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