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In statistics, Deming regression, named after W. Edwards Deming, is an errors-in-variables model that tries to find the line of best fit for a two-dimensional data set. It differs from the simple linear regression in that it accounts for errors in observations on both the x - and the y - axis.
It is a generalization of Deming regression and also of orthogonal regression, and can be applied to both linear and non-linear models. The total least squares approximation of the data is generically equivalent to the best, in the Frobenius norm , low-rank approximation of the data matrix.
In Deming regression, a type of linear curve fitting, if the dependent and independent variables have equal variance this results in orthogonal regression in which the degree of imperfection of the fit is measured for each data point as the perpendicular distance of the point from the regression line.
Control charts are graphical plots used in production control to determine whether quality and manufacturing processes are being controlled under stable conditions. (ISO 7870-1) [1] The hourly status is arranged on the graph, and the occurrence of abnormalities is judged based on the presence of data that differs from the conventional trend or deviates from the control limit line.
Linear errors-in-variables models were studied first, probably because linear models were so widely used and they are easier than non-linear ones. Unlike standard least squares regression (OLS), extending errors in variables regression (EiV) from the simple to the multivariable case is not straightforward, unless one treats all variables in the same way i.e. assume equal reliability.
It may be considered a robust version of reduced major axis regression. The slope estimator b {\displaystyle b} is the median of the absolute values of all pairwise slopes. The original algorithm is rather slow for larger data sets as its computational complexity is O ( n 2 ) {\displaystyle O(n^{2})} .
Vertical distance: Simple linear regression; Resistance to outliers: Robust simple linear regression; Perpendicular distance: Orthogonal regression (this is not scale-invariant i.e. changing the measurement units leads to a different line.) Weighted geometric distance: Deming regression
Analyse-it Method Validation edition provides the standard Analyse-it statistical analyses above, plus procedures for method evaluation, validation and demonstration, including Bland–Altman bias plots, Linear regression, Weighted Linear regression, Deming regression, Weighted Deming regression and Passing Bablok for method comparison ...