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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.
DeFries–Fulker regression; de Moivre's law; De Moivre–Laplace theorem; Decision boundary; Decision theory; Decomposition of time series; Degenerate distribution; Degrees of freedom (statistics) Delaporte distribution; Delphi method; Delta method; Demand forecasting; Deming regression; Demographics; Demography. Demographic statistics ...
Download as PDF; Printable version; ... Pages in category "Regression analysis" ... Deming regression; Dependent and independent variables;
Deming regression — assumes that the ratio δ = σ² ε /σ² η is known. This could be appropriate for example when errors in y and x are both caused by measurements, and the accuracy of measuring devices or procedures are known.
Deming regression (total least squares) also finds a line that fits a set of two-dimensional sample points, but (unlike ordinary least squares, least absolute deviations, and median slope regression) it is not really an instance of simple linear regression, because it does not separate the coordinates into one dependent and one independent ...
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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 ...