Deming Regression. Deming Regression In ordinary linear regression the yi values are estimated from the xi values with error ɛi. In this case Deming regression minimizes the sum of the squares of the perpendicular distances of the points from the line.
Jan 23 2016 Deming regression is based on maximum likelihood estimation and it is used for fitting a line on measurement data when both X and Y have measurement errors. This is also called orthogonal regression. In Deming regression it is assumed that also the xi values are estimated with error.
We further assume that the ɛi and δi errors are independent of each other and both are distributed normally with mean zero.
What is Deming regression. In this case Deming regression minimizes the sum of the squares of the perpendicular distances of the points from the line. In Deming regression it is assumed that also the xi values are estimated with error which we will denote δi. Deming regression is an errors-in-variables model that fits a line describing the relationship between two variables.
