IPW-based robust estimation of the SAR model with missing data

2021 ◽  
Vol 172 ◽  
pp. 109065
Author(s):  
Guowang Luo ◽  
Mixia Wu ◽  
Liwen Xu
Keyword(s):  
Missing Data ◽  
Robust Estimation ◽  
Sar Model

scholarly journals Adjustment for Missing Data in Complex Surveys Using Doubly Robust Estimation

Epidemiology ◽  
2010 ◽  
Vol 21 (6) ◽  
pp. 863-871 ◽  
Author(s):  
Kathleen E. Wirth ◽  
Eric J. Tchetgen Tchetgen ◽  
Megan Murray
Keyword(s):  
Missing Data ◽  
Robust Estimation ◽  
Complex Surveys ◽  
Doubly Robust Estimation ◽  
Doubly Robust

Robust estimation of traffic density with missing data using an adaptive-R extended Kalman filter

2022 ◽  
Vol 421 ◽  
pp. 126915
Author(s):  
A.S.M. Bakibillah ◽  
Yong Hwa Tan ◽  
Junn Yong Loo ◽  
Chee Pin Tan ◽  
M.A.S. Kamal ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Missing Data ◽  
Extended Kalman Filter ◽  
Robust Estimation ◽  
Traffic Density

A Review of Multiply Robust Estimation with Missing Data

2021 ◽  
pp. 103-118
Author(s):  
Sixia Chen ◽  
David Haziza
Keyword(s):  
Missing Data ◽  
Robust Estimation

Gross Error Positioning and Processing Method Based on Forest Grey Modeling

2011 ◽  
Vol 80-81 ◽  
pp. 1262-1267
Author(s):  
Yong Li ◽  
Zhan Wu Wang ◽  
Shuang Ning Tang
Keyword(s):  
Missing Data ◽  
Robust Estimation ◽  
Forest Fire ◽  
Estimation Theory ◽  
Processing Method ◽  
Gross Error ◽  
Modeling Data

The paper is committed to overcome the influence of gross error on the small quantity data of forest fire grey modeling. According to the quantity of the modeling data, Grey judgment of gross error and robust estimation theory is used separately for finding the gross error exit whether or not from the modeling data. And robust estimation theory and LIR algorithm can be used to process the gross error. From the examples, A quarter of fitting precision of robust estimation is less than 1%, and 75% is 1～5%; and half of fitting precision of LIR algorithm is less than 1%, and half is 1～5%. That is to say LIR algorithm provides a rapid, simple and practical way to build model of data which contains gross error or which contain missing data.

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