PARAMETERS ESTIMATION OF AUTOREGRESSION WITH STRUCTURED TOTAL LEAST SQUARES
Hu Chuan 1) ; and Chen Yi1,2)
1)College of Surveying and Geoinformatics, Tongji University, Shanghai 200092;2)Key Laboratory of Modern Engineering Surveying, SBSM, Shanghai 200092
Abstract The structured total least squares not only take into account the errors of coefficient but also consider the identical elements have attained the same correction value in coefficient or in argument of vector of observation L and coefficient matrix A. This method make the adjustment theory more strict than others such as least squares and total least squares.In this contribution that we give an simply iteration algorithm for structured total least squares,and give a numerical example to demonstrate the efficiency and feasibility,as well as the advantages of the structured total least squares for AutoRegresion parameters estimation at last .
Key words ：
autoregresion
structured total least squares
parameters estimation
observation vector
coefficient matrix
Received: 01 January 1900
Corresponding Authors:
Hu Chuan
Cite this article:
Hu Chuan ,and Chen Yi. PARAMETERS ESTIMATION OF AUTOREGRESSION WITH STRUCTURED TOTAL LEAST SQUARES[J]. , 2013, 33(1): 45-47.
Hu Chuan ,and Chen Yi. PARAMETERS ESTIMATION OF AUTOREGRESSION WITH STRUCTURED TOTAL LEAST SQUARES[J]. jgg, 2013, 33(1): 45-47.
URL:
http://www.jgg09.com/EN/ OR http://www.jgg09.com/EN/Y2013/V33/I1/45
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