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In regression analysis, the distinction between errors and residuals is subtle and important, and leads to the concept of studentized residuals. Given an unobservable function that relates the independent variable to the dependent variable – say, a line – the deviations of the dependent variable observations from this function are the ...
Least absolute deviations (LAD), also known as least absolute errors (LAE), least absolute residuals (LAR), or least absolute values (LAV), is a statistical optimality criterion and a statistical optimization technique based on minimizing the sum of absolute deviations (also sum of absolute residuals or sum of absolute errors) or the L 1 norm of such values.
Download as PDF; Printable version; ... For absolute errors, ... Errors and residuals in statistics; Experimental uncertainty analysis;
Download as PDF; Printable version; ... root mean squared error, mean absolute percentage error, ... Errors and residuals in statistics;
IRLS is used to find the maximum likelihood estimates of a generalized linear model, and in robust regression to find an M-estimator, as a way of mitigating the influence of outliers in an otherwise normally-distributed data set, for example, by minimizing the least absolute errors rather than the least square errors.
Download as PDF; Printable version; In other projects Wikidata item; Appearance. move to sidebar hide ... MAE is calculated as the sum of absolute errors (i.e., ...
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Download as PDF; Printable version; ... Pages in category "Errors and residuals" ... Mean absolute error; N. Non-sampling error; O.