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.
Farlex Partner Medical Dictionary © Farlex 2012
References in periodicals archive ?
A least squares fit can be done to the scattered data as follows.
The linear least squares fit to the data shows that a sample of 0% crystallinity by density has a crystallinity of 3% by XRD.
The particle diameter was determined from a nonlinear least squares fit of the predicted scattering based on Mie theory and the measured data.
Position and width can also be included as parameters in a either a non-linear least squares fit by sequential simplex for example (23) or by including first and second derivative profiles in a linear fit (24).
Solid lines show the least squares fits, whereas the two dashed lines show the range of one standard deviation.
The straight lines are weighted least squares fits to a power law, -[DELTA][R.sub.H] = s[R.sub.x.sup.[delta]].
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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