least squares

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least squares

(lēst skwārz),
A principle of estimation invented by Gauss in which the estimates of a set of parameters in a statistical model are the quantities that minimize the sum of squared differences between the observed values of the dependent variable and the values predicted by the model.

least squares

a method of regression analysis. The line on a graph that best summarizes the relationship between two variables is the one that ensures that there is the least value of the sum of the squares of the deviation between the fitted curve and each of the original data points.
References in periodicals archive ?
The tensor product of the B-splines is computed at the data points, a least squares fit is made to the data, and the current absolute residuals of the fit are computed at each data point.
The straight lines are weighted least squares fits to a power law, -[DELTA][R.
Subsequent chapters feature coverage of linear transformations from Rn to Rm, the geometry of linear and affine transformations, least squares fits and pseudoinverses, and eigenvalues and eigenvectors.
This should reduce the number of extraneous parameters when performing least squares fits, thereby improving the significance of the remaining parameters.

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