scholarly journals The least-squares ambiguity decorrelation adjustment: its performance on short GPS baselines and short observation spans

1997 ◽  
Vol 71 (10) ◽  
pp. 589-602 ◽  
Author(s):  
P. J. G. Teunissen ◽  
C. C. J. M. Tiberius ◽  
P. J. de Jonge
Keyword(s):  
Least Squares ◽  
Ambiguity Decorrelation

The Application of MLAMBDA for Time Series Radar Interferometry

2012 ◽  
Vol 532-533 ◽  
pp. 1031-1035
Author(s):  
Jing Qin Mu ◽  
Sheng Zhan
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Least Squares ◽  
Radar Interferometry ◽  
Phase Ambiguity ◽  
Series Analysis ◽  
Ambiguity Decorrelation

The time series analysis for D-InSAR is a new kind of method. While modeling with Gauss-Markoff model and estimating parameters, how to search for integer phase ambiguity needs to be addressed. In the study, the modified least-squares ambiguity decorrelation adjustment algorithm (MLAMBDA) is applied for the optimal integer phase ambiguity. The problems about applying are analyzed and solved by many experiments. At last, the method is applied for the project of all Tianjin district and the result is correct and effective.

Heteroscedastic Methods for Performing All Pairwise Comparisons of Regression Lines Associated With J Independent Groups

Methodology ◽  
2015 ◽  
Vol 11 (3) ◽  
pp. 110-115 ◽  
Author(s):  
Rand R. Wilcox ◽  
Jinxia Ma
Keyword(s):  
Least Squares ◽  
Pairwise Comparisons ◽  
Simple Extension ◽  
Type I ◽  
Type I Errors ◽  
Well Elderly ◽  
Using Data

Abstract. The paper compares methods that allow both within group and between group heteroscedasticity when performing all pairwise comparisons of the least squares lines associated with J independent groups. The methods are based on simple extension of results derived by Johansen (1980) and Welch (1938) in conjunction with the HC3 and HC4 estimators. The probability of one or more Type I errors is controlled using the improvement on the Bonferroni method derived by Hochberg (1988) . Results are illustrated using data from the Well Elderly 2 study, which motivated this paper.

An fMRI study examining spatial navigation through a virtual environment: Partial least squares analysis

2005 ◽  
Author(s):  
Richard Mraz ◽  
Nancy J. Lobaugh ◽  
Genevieve Quintin ◽  
Konstantine K. Kakzanis ◽  
Simon J. Graham
Keyword(s):  
Least Squares ◽  
Virtual Environment ◽  
Partial Least Squares ◽  
Spatial Navigation ◽  
Partial Least Squares Analysis ◽  
Fmri Study

‘Least squares’ method—theorem or law?

1980 ◽  
Vol 59 (9) ◽  
pp. 8
Author(s):  
D.E. Turnbull
Keyword(s):  
Least Squares ◽  
Least Squares Method
Sign in / Sign up

Export Citation Format

Share Document