A solution for the least-squares fit of a straight line to measurements in two dimensions is presented for the case where measurements have uncorrelated errors in both variables, while all errors in a given variable are taken from the same probability distribution. The straight line solution is parametrized either by the intercept and the slope or by the impact parameter relative to the origin and the angle with respect to one axis. Simple formulas are presented for both the estimated fit parameters and their standard errors
In this contribution the fitting of a straight line to 3D point data is considered, with Cartesian c...
Author Institution: Centre for Experimental and Constructive Mathematics, Department of Mathematics,...
Abstract. Bounds on the error of certain penalized least squares data setting, more detailed results...
In this paper errors in variables methods for fitting straight lines to data are reviewed. In these ...
In this paper errors in variables methods for fitting straight lines to data are reviewed. In these ...
In this paper errors in variables methods for fitting straight lines to data are reviewed. In these ...
In this paper errors in variables methods for fitting straight lines to data are reviewed. In these ...
In this paper errors in variables methods for fitting straight lines to data are reviewed. In these ...
The Method of Least Squares is a procedure to determine the best fit line to data; the proof uses si...
Least‐squares fitting is reviewed, in tutorial form, when both variables contain significant errors....
Least‐squares fitting is reviewed, in tutorial form, when both variables contain significant errors....
A fundamental problem in data analysis is that of fitting a given model to observed data. It is comm...
Fitting a surface to a given set of measurements is an essential function for engineers and geodesis...
Abstract – In the field of metrology it is common practice to approximate the results of a measureme...
The moving least-squares (MLS) method has been developed for fitting measurement data contaminated w...
In this contribution the fitting of a straight line to 3D point data is considered, with Cartesian c...
Author Institution: Centre for Experimental and Constructive Mathematics, Department of Mathematics,...
Abstract. Bounds on the error of certain penalized least squares data setting, more detailed results...
In this paper errors in variables methods for fitting straight lines to data are reviewed. In these ...
In this paper errors in variables methods for fitting straight lines to data are reviewed. In these ...
In this paper errors in variables methods for fitting straight lines to data are reviewed. In these ...
In this paper errors in variables methods for fitting straight lines to data are reviewed. In these ...
In this paper errors in variables methods for fitting straight lines to data are reviewed. In these ...
The Method of Least Squares is a procedure to determine the best fit line to data; the proof uses si...
Least‐squares fitting is reviewed, in tutorial form, when both variables contain significant errors....
Least‐squares fitting is reviewed, in tutorial form, when both variables contain significant errors....
A fundamental problem in data analysis is that of fitting a given model to observed data. It is comm...
Fitting a surface to a given set of measurements is an essential function for engineers and geodesis...
Abstract – In the field of metrology it is common practice to approximate the results of a measureme...
The moving least-squares (MLS) method has been developed for fitting measurement data contaminated w...
In this contribution the fitting of a straight line to 3D point data is considered, with Cartesian c...
Author Institution: Centre for Experimental and Constructive Mathematics, Department of Mathematics,...
Abstract. Bounds on the error of certain penalized least squares data setting, more detailed results...